Dissertations / Theses on the topic 'Features of video information'
To see the other types of publications on this topic, follow the link: Features of video information.
Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles
Consult the top 50 dissertations / theses for your research on the topic 'Features of video information.'
Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.
You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.
Browse dissertations / theses on a wide variety of disciplines and organise your bibliography correctly.
1
Asghar, Muhammad Nabeel. "Feature based dynamic intra-video indexing." Thesis, University of Bedfordshire, 2014. http://hdl.handle.net/10547/338913.
Full textAbstract:
With the advent of digital imagery and its wide spread application in all vistas of life, it has become an important component in the world of communication. Video content ranging from broadcast news, sports, personal videos, surveillance, movies and entertainment and similar domains is increasing exponentially in quantity and it is becoming a challenge to retrieve content of interest from the corpora. This has led to an increased interest amongst the researchers to investigate concepts of video structure analysis, feature extraction, content annotation, tagging, video indexing, querying and retrieval to fulfil the requirements. However, most of the previous work is confined within specific domain and constrained by the quality, processing and storage capabilities. This thesis presents a novel framework agglomerating the established approaches from feature extraction to browsing in one system of content based video retrieval. The proposed framework significantly fills the gap identified while satisfying the imposed constraints of processing, storage, quality and retrieval times. The output entails a framework, methodology and prototype application to allow the user to efficiently and effectively retrieved content of interest such as age, gender and activity by specifying the relevant query. Experiments have shown plausible results with an average precision and recall of 0.91 and 0.92 respectively for face detection using Haar wavelets based approach. Precision of age ranges from 0.82 to 0.91 and recall from 0.78 to 0.84. The recognition of gender gives better precision with males (0.89) compared to females while recall gives a higher value with females (0.92). Activity of the subject has been detected using Hough transform and classified using Hiddell Markov Model. A comprehensive dataset to support similar studies has also been developed as part of the research process. A Graphical User Interface (GUI) providing a friendly and intuitive interface has been integrated into the developed system to facilitate the retrieval process. The comparison results of the intraclass correlation coefficient (ICC) shows that the performance of the system closely resembles with that of the human annotator. The performance has been optimised for time and error rate.
2
Sjöblom, Mattias. "Investigating Gaze Attraction to Bottom-Up Visual Features for Visual Aids in Games." Thesis, Blekinge Tekniska Högskola, Institutionen för kreativa teknologier, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-12862.
Full textAbstract:
Context. Video games usually have visual aids guiding the players in 3D-environments. The designers need to know which visual feature is the most effective in attracting a player's gaze and what features are preferred by players as visual aid. Objectives. This study investigates which feature of the bottom-upvisual attention process attracts the gaze faster. Methods. With the use of the Tobii T60 eye tracking system, a user study with 32 participants was conducted in a controlled environment. An experiment was created where each participant looked at a slideshow consisting of 18 pictures with 8 objects on each picture. One object per picture had a bottom-up visual feature applied that made it stand out as different. Video games often have a goal or a task and to connect the experiment to video games a goal was set. This goal was to find the object with the visual feature applied. The eye tracker measured the gaze while the participant was trying to find the object. A survey to determine which visual feature was preferredby the players was also made. Results. The result showed that colour was the visual feature with the shortest time to attract attention. It was closely followed by intensity,motion and a pulsating highlight. Small size had the longest attraction time. Results also showed that the preferred visual feature for visual aid by the players was intensity and the least preferred was orientation. Conclusions. The results show that visual features with contrast changes in the texture seems to draw attention faster, with colour the fastest, than changes on the object itself. These features were also the most preferred as visual aid by the players with intensity the most preferred. If this study was done on a larger scale within a 3D-environment, this experiment could show promise to help designers in decisions regarding visual aid in video games.
3
Gurrapu, Chaitanya. "Human Action Recognition In Video Data For Surveillance Applications." Queensland University of Technology, 2004. http://eprints.qut.edu.au/15878/.
Full textAbstract:
Detecting human actions using a camera has many possible applications in the security industry. When a human performs an action, his/her body goes through a signature sequence of poses. To detect these pose changes and hence the activities performed, a pattern recogniser needs to be built into the video system. Due to the temporal nature of the patterns, Hidden Markov Models (HMM), used extensively in speech recognition, were investigated. Initially a gesture recognition system was built using novel features. These features were obtained by approximating the contour of the foreground object with a polygon and extracting the polygon's vertices. A Gaussian Mixture Model (GMM) was fit to the vertices obtained from a few frames and the parameters of the GMM itself were used as features for the HMM. A more practical activity detection system using a more sophisticated foreground segmentation algorithm immune to varying lighting conditions and permanent changes to the foreground was then built. The foreground segmentation algorithm models each of the pixel values using clusters and continually uses incoming pixels to update the cluster parameters. Cast shadows were identified and removed by assuming that shadow regions were less likely to produce strong edges in the image than real objects and that this likelihood further decreases after colour segmentation. Colour segmentation itself was performed by clustering together pixel values in the feature space using a gradient ascent algorithm called mean shift. More robust features in the form of mesh features were also obtained by dividing the bounding box of the binarised object into grid elements and calculating the ratio of foreground to background pixels in each of the grid elements. These features were vector quantized to reduce their dimensionality and the resulting symbols presented as features to the HMM to achieve a recognition rate of 62% for an event involving a person writing on a white board. The recognition rate increased to 80% for the "seen" person sequences, i.e. the sequences of the person used to train the models. With a fixed lighting position, the lack of a shadow removal subsystem improved the detection rate. This is because of the consistent profile of the shadows in both the training and testing sequences due to the fixed lighting positions. Even with a lower recognition rate, the shadow removal subsystem was considered an indispensable part of a practical, generic surveillance system.
4
Johansson, Henrik. "Video Flow Classification : Feature Based Classification Using the Tree-based Approach." Thesis, Karlstads universitet, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kau:diva-43012.
Full textAbstract:
This dissertation describes a study which aims to classify video flows from Internet network traffic. In this study, classification is done based on the characteristics of the flow, which includes features such as payload sizes and inter-arrival time. The purpose of this is to give an alternative to classifying flows based on the contents of their payload packets. Because of an increase of encrypted flows within Internet network traffic, this is a necessity. Data with known class is fed to a machine learning classifier such that a model can be created. This model can then be used for classification of new unknown data. For this study, two different classifiers are used, namely decision trees and random forest. Several tests are completed to attain the best possible models. The results of this dissertation shows that classification based on characteristics is possible and the random forest classifier in particular achieves good accuracies. However, the accuracy of classification of encrypted flows was not able to be tested within this project.HITS, 4707
5
Копинець, Валеріян Валеріянович. "Особливості оброблення відеоінформації для мультимедійних видань мистецького спрямування." Master's thesis, КПІ ім. Ігоря Сікорського, 2020. https://ela.kpi.ua/handle/123456789/39436.
Full textAbstract:
Пояснювальна записка до магістерської дисертації на тему «Особливості
оброблення відеоінформації для мультимедійних видань мистецького
спрямування», містить сторінок 72, рисунків 22, таблиць 24, літературних
джерел 16.
Виконано інтеграцію відеоекскурсії у форматі 360 на базі технології
доповненої реальності. Досліджено основні особливості оброблення
відеоінформації. Виготовлено електронний та фізичний примірник (сторінку)
видання для демонстрації. Наведено техніко-економічне обґрунтування
проекту. Розраховано термін окупності проекту та стартап-план.Explanatory note to the master's dissertation on "Features of video information processing for multimedia publications in the field of art", contains 72 pages, drawings 22, tables 24, literature sources 16. Integrated video tour in 360 format based on augmented reality technology. The main features of video information processing are investigated. An electronic and physical copy (page) of the publication was made for demonstration. Feasibility study of the project is given. The payback period of the project and the startup plan are calculated.
6
Šabatka, Pavel. "Vyhledávání informací." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2010. http://www.nusl.cz/ntk/nusl-237213.
Full textAbstract:
The purpose of this thesis is a summary of theoretical knowledge in the field of information retrieval. This document contains mathematical models that can be used for information retrieval algorithms, including how to rank them. There are also examined the specifics of image and text data. The practical part is then an implementation of the algorithm in video shots of the TRECVid 2009 dataset based on high-level features. The uniqueness of this algorithm is to use internet search engines to obtain terms similarity. The work contains a detailed description of the implemented algorithm including the process of tuning and conclusions of its testing.
7
Grinberg, Michael [Verfasser]. "Feature-Based Probabilistic Data Association for Video-Based Multi-Object Tracking / Michael Grinberg." Karlsruhe : KIT Scientific Publishing, 2018. http://www.ksp.kit.edu.
Full text
8
Mohanna, Farahnaz. "Content based video database retrieval using shape features." Thesis, University of Surrey, 2002. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.250764.
Full text
9
Nallabolu, Adithya Reddy. "Unsupervised Learning of Spatiotemporal Features by Video Completion." Thesis, Virginia Tech, 2017. http://hdl.handle.net/10919/79702.
Full textAbstract:
In this work, we present an unsupervised representation learning approach for learning rich spatiotemporal features from videos without the supervision from semantic labels. We propose to learn the spatiotemporal features by training a 3D convolutional neural network (CNN) using video completion as a surrogate task. Using a large collection of unlabeled videos, we train the CNN to predict the missing pixels of a spatiotemporal hole given the remaining parts of the video through minimizing per-pixel reconstruction loss. To achieve good reconstruction results using color videos, the CNN needs to have a certain level of understanding of the scene dynamics and predict plausible, temporally coherent contents. We further explore to jointly reconstruct both color frames and flow fields. By exploiting the statistical temporal structure of images, we show that the learned representations capture meaningful spatiotemporal structures from raw videos. We validate the effectiveness of our approach for CNN pre-training on action recognition and action similarity labeling problems. Our quantitative results demonstrate that our method compares favorably against learning without external data and existing unsupervised learning approaches.Master of Science
10
Černý, Petr. "Vyhledávání ve videu." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2012. http://www.nusl.cz/ntk/nusl-236590.
Full textAbstract:
This thesis summarizes the information retrieval theory, the relational model basic and focuses on the data indexing in relational database systems. The thesis focuses on multimedia data searching. It includes description of automatic multimedia data content extraction and multimedia data indexing. Practical part discusses design and solution implementation for improving query effectivity for multidimensional vector similarity which describes multimedia data. Thesis final part discusses experiments with this solution.
11
Jianshu, Chao [Verfasser], Eckehard [Akademischer Betreuer] Steinbach, and Matteo [Akademischer Betreuer] Cesana. "Feature-preserving image and video compression / Chao Jianshu. Betreuer: Eckehard Steinbach. Gutachter: Matteo Cesana ; Eckehard Steinbach." München : Universitätsbibliothek der TU München, 2016. http://d-nb.info/1088725104/34.
Full text
12
Chen, Bo. "Deep learning of invariant spatio-temporal features from video." Thesis, University of British Columbia, 2010. http://hdl.handle.net/2429/27651.
Full textAbstract:
We present a novel hierarchical and distributed model for learning invariant spatio-temporal features from video. Our approach builds on previous deep learning methods and uses the Convolutional Restricted Boltzmann machine (CRBM) as a building block. Our model, called the Space-Time Deep Belief Network (ST-DBN), aggregates over both space and time in an alternating way so that higher layers capture more distant events in space and time. The model is learned in an unsupervised manner. The experiments show that it has good invariance properties, that it is well-suited for recognition tasks, and that it has reasonable generative properties that enable it to denoise video and produce spatio-temporal predictions.
13
Comstedt, Erik. "Effect of additional compression features on h.264 surveillance video." Thesis, Mittuniversitetet, Avdelningen för informationssystem och -teknologi, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-30901.
Full textAbstract:
In video surveillance business, a recurring topic of discussion is quality versus data usage. A higher quality allows for more details to be captured at the cost of a higher bit rate, and for cameras monitoring events 24 hours a day, limiting data usage can quickly become a factor to consider. The purpose of this thesis has been to apply additional compression features to a h.264 video steam, and evaluate their effects on the videos overall quality. Using a surveillance camera, recordings of video streams were obtained. These recordings had constant GOP and frame rates. By breaking down one of these videos to an image sequence, it was possible to encode the image sequence into video streams with variable GOP/FPS using the software Ffmpeg. Additionally a user test was performed on these video streams, following the DSCQS standard from the ITU-R recom- mendation. The participants had to subjectively determine the quality of video streams. The results from the these tests showed that the participants did not no- tice any considerable difference in quality between the normal videos and the videos with variable GOP/FPS. Based of these results, the thesis has shown that that additional compression features can be applied to h.264 surveillance streams, without having a substantial effect on the video streams overall quality.
14
Yilmazturk, Mehmet Celaleddin. "Online And Semi-automatic Annotation Of Faces In Personal Videos." Master's thesis, METU, 2010. http://etd.lib.metu.edu.tr/upload/12611936/index.pdf.
Full textAbstract:
Video annotation has become an important issue due to the rapidly increasing amount of video available. For efficient video content searches, annotation has to be done beforehand, which is a time-consuming process if done manually. Automatic annotation of faces for person identification is a major challenge in the context of content-based video retrieval. This thesis work focuses on the development of a semi-automatic face annotation system which benefits from online learning methods. The system creates a face database by using face detection and tracking algorithms to collect samples of the encountered faces in the video and by receiving labels from the user. Using this database a learner model is trained. While the training session continues, the system starts offering labels for the newly encountered faces and lets the user acknowledge or correct the suggested labels hence a learner is updated online throughout the video. The user is free to train the learner until satisfactory results are obtained. In order to create a face database, a shot boundary algorithm is implemented to partition the video into semantically meaningful segments and the user browses through the video from one shot boundary to the next. A face detector followed by a face tracker is implemented to collect face samples within two shot boundary frames. For online learning, feature extraction and classification methods which are computationally efficient are investigated and evaluated. Sequential variants of some robust batch classification algorithms are implemented. Combinations of feature extraction and classification methods have been tested and compared according to their face recognition accuracy and computational performances.
15
Clark, Angus Alistair. "Region classification for the interpretation of video sequences." Thesis, University of Bristol, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.302167.
Full text
16
Moroz, Viktor. "Features of information security in martial law." Thesis, National Aviation University, 2021. https://er.nau.edu.ua/handle/NAU/53731.
Full textAbstract:
Purpose: the article is devoted to the analyze of the features of information security in martial law.
Research methods: comparative analysis of individual regulations and the case law of Ukraine regulatory
framework and case law in the application of the information security in martial law. Results: normative
regulation of the formation of a single information space in Ukraine should contribute to the harmonious
development of information resources, information services and the information product in the country.
Improving the effectiveness of the subjects under investigation countering threats to information security.
Discussion: the analysis of the legal the features of information security in martial law is carried out.
17
Thelin, Robert. "Interactive Video in Online Education : Evaluation of Current Video Delivery Systems for Interactive Features Defined in Literature." Thesis, Umeå universitet, Institutionen för datavetenskap, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-128304.
Full textAbstract:
Increasingly lectures are being offered online in the form of online lecture videos. Although more and more lectures are now being offered online in the form of videos, they tend to be mostly non-interactive and linear. This thesis examines current approaches to online learning and evaluate current video delivery services to determine if they can support the kind of interactive features that are defined in the literature. The thesis shows that the video delivery services can be used to integrate interactive elements, but will do so by being used together with other technologies, such as HTML5.
18
Gupta, Ankur. "Using line and ellipse features for rectification of broadcast hockey video." Thesis, University of British Columbia, 2010. http://hdl.handle.net/2429/30490.
Full textAbstract:
To use hockey broadcast videos for automatic game analysis, we need to compensate for camera viewpoint and motion. This can be done by using features on the rink to estimate the homography between the observed rink and a geometric model of the rink, as specified in the appropriate rule book (top down view of the rink). However, occlusion due to players, wide range of camera motion and frames with few reliable key-points pose a significant challenge for robustness and accuracy of the solution. In this work, we describe a new method to use line and ellipse features along with key-point based matches to estimate the homography. We combine domain knowledge (i.e., rink geometry) with an appearance model of the rink to detect these features accurately. This overdetermines the homography estimation to make the system more robust. We show this approach is applicable to real world data and demonstrate the ability to track long sequences on the order of 1,000 frames.
19
Guan, Hao. "Local features, structure-from-motion and view synthesis in spherical video." Thesis, University of York, 2016. http://etheses.whiterose.ac.uk/17414/.
Full textAbstract:
This thesis addresses the problem of synthesising new views from spherical video or image sequences. We propose an interest point detector and feature descriptor that allows us to robustly match local features between pairs of spherical images and use this as part of a structure-from-motion pipeline that allows us to estimate camera pose from a spherical video sequence. With pose estimates to hand, we propose methods for view stabilisation and novel viewpoint synthesis. In Chapter 3 we describe our contribution in the area of feature detection and description in spherical images. First, we present a novel representation for spherical images which uses a discrete geodesic grid composed of hexagonal pixels. Second, we extend the BRISK binary descriptor to the sphere, proposing methods for multiscale corner detection, sub-pixel position and sub-octave scale refinement and descriptor construction in the tangent space to the sphere. In Chapter 4 we describe our contributions in the area of spherical structure-from-motion. We revisit problems from multiview geometry in the context of spherical images. We propose methods suited to spherical camera geometry for the spherical-n-point problem and calibrated spherical reconstruction. We introduce a new probabilistic interpretation of spherical structure-from-motion which uses the von Mises-Fisher distribution in spherical feature point positions. This model provides an alternate objective function that we use in bundle adjustment. In Chapter 5 we describe our contributions in the area of view synthesis from spherical images. We exploit the camera pose estimates made by our pipeline and use these in two view synthesis applications. The first is view stabilisation where we remove the effect of viewing direction changes, often present in first person video. Second, we propose a method for synthesising novel viewpoints.
20
Iyengar, Giridharan Ranganathan 1969. "Information theoretic measures for encoding video." Thesis, Massachusetts Institute of Technology, 1995. http://hdl.handle.net/1721.1/61531.
Full text
21
Isaieva, O. A., and О. Г. Аврунін. "Video dermoscopy study of the skin." Thesis, Liverpool, United Kingdom, 2019. http://openarchive.nure.ua/handle/document/10265.
Full textAbstract:
The work is devoted to the study of the main pathologies of the skin, the possibility of diagnosing them using video dermatoscopy. Determining the differences between digital dermoscopy and video dermoscopy. The difference between the diagnosis of common skin diseases from malignant and tumors is considered. The science of fluorescent technology is being studied. The diagnostic capabilities of digital dermatoscopy are discussed.
22
Banda, Nagamani. "Adaptive video segmentation." Morgantown, W. Va. : [West Virginia University Libraries], 2004. https://etd.wvu.edu/etd/controller.jsp?moduleName=documentdata&jsp%5FetdId=3520.
Full textAbstract:
Thesis (M.S.)--West Virginia University, 2004.Title from document title page. Document formatted into pages; contains vi, 52 p. : ill. (some col.). Includes abstract. Includes bibliographical references (p. 50-52).
23
Kovesi, Peter. "Invariant measures of image features from phase information." University of Western Australia. Dept. of Computer Science, 1996. http://theses.library.uwa.edu.au/adt-WU2003.0006.
Full textAbstract:
If reliable and general computer vision techniques are to be developed it is crucial that we find ways of characterizing low-level image features with invariant quantities. For example, if edge significance could be measured in a way that was invariant to image illumination and contrast, higher-level image processing operations could be conducted with much greater confidence. However, despite their importance, little attention has been paid to the need for invariant quantities in low-level vision for tasks such as feature detection or feature matching. This thesis develops a number of invariant low-level image measures for feature detection, local symmetry/asymmetry detection, and for signal matching. These invariant quantities are developed from representations of the image in the frequency domain. In particular, phase data is used as the fundamental building block for constructing these measures. Phase congruency is developed as an illumination and contrast invariant measure of feature significance. This allows edges, lines and other features to be detected reliably, and fixed thresholds can be applied over wide classes of images. Points of local symmetry and asymmetry in images give rise to special arrangements of phase, and these too can be characterized by invariant measures. Finally, a new approach to signal matching that uses correlation of local phase and amplitude information is developed. This approach allows reliable phase based disparity measurements to be made, overcoming many of the difficulties associated with scale-space singularities.
24
Korpinen, K. P. (Kalle-Pekka). "Projektinhallinan video yliopisto-opetuksessa." Master's thesis, University of Oulu, 2014. http://urn.fi/URN:NBN:fi:oulu-201405241497.
Full textAbstract:
Tutkielman tavoitteena oli selvittää millainen video auttaa yliopisto-opiskelijaa ymmärtämään projektinhallinnan keskeisten osa-alueiden tärkeyden? Tämä tutkielma toteutettiin kyselytutkimuksena, jota täydennettiin teemahaastatteluilla.
Lähtökohtana kyselylle oli projektiryhmän tuotos syksyn 2012 Projekti II kurssilla. Projektiryhmä tuotti projektityöskentelyä kuvaavan videon Big Things Have Small Beginnings, joka otettiin käyttöön osaksi kyseisen kurssin opiskelumateriaalia. Tämän myötä tuli esille halu selvittää kuinka opiskelijat kokevat kyseisen videotuotoksen opiskelumateriaalina: kuinka projektinhallinnan video on auttanut ymmärtämään eri projektihallinnan osa-alueita?
Tässä tutkimuksessa kyselytutkimuksella evaluoitiin projektinhallinnan videota, joka on osa Oulun yliopiston Tietojenkäsittelytieteidenlaitoksen Projekti II kurssin opetusmateriaalia. Videon ymmärrettävyyttä testattiin tutkimuksessa suoritetuilla kyselyillä. Vastaajat kyselyissä olivat Tietojenkäsittelytieteidenlaitoksen Projekti II kurssin opiskelijoita. Vastausten perusteella voidaan arvioida, että videon avulla opiskelijat olivat ymmärtäneet eri projektinhallintaa osa-alueet pääosin todella positiivisesti. Voidaan myös arvioida, että videota pidettiin opettavaisena ja sitä oli pidetty hyvänä lisänä aloitusluennolle. Tutkimuksen merkittävyydestä voidaan todeta, että opiskelijoiden tuotos on otettu osaksi yliopisto-opetuksen opetusmateriaalia. Hyvä palaute videosta opetusmateriaalina voi edesauttaa opiskelijavetoisten materiaalien tuottamista yliopisto-opetuksessa jatkossakin.
Haasteena tässä tutkielmassa on ollut löytää vastaavia tutkimuksia, kuin tämä tutkielma on. Näin ollen tässä tutkielmassa on keskitytty yleisimmin multimediamateriaaleihin ja keskittyen lisäksi erityisesti videomateriaaleihin. Myös huumori on tuotu esille johtuen tuotetun videon humoristisesta luonteesta.
25
Castagno, Roberto. "Video segmentation based on multiple features for interactive and automatic multimedia applications /." Lausanne : Ecole polytechnique fédérale, 1998. http://library.epfl.ch/theses/?nr=1894.
Full text
26
Maniccam, Suchindran S. "Image-video compression, encryption and information hiding /." Online version via UMI:, 2001.
Find full text
27
Wampler, Christopher. "Information leakage in encrypted IP video traffic." Thesis, Georgia Institute of Technology, 2014. http://hdl.handle.net/1853/54287.
Full textAbstract:
We show that information leakage occurs in video over IP traffic, including for encrypted payloads. It is possible to detect events occurring in the field of view of a camera streaming live video through analysis of network traffic metadata including arrival time between packets, packets sizes, and video stream bandwidth. Event detection through metadata analysis is possible even when common encryption techniques are applied to the video stream such as SSL or AES. We have observed information leakage across multiple codes and cameras. Through timestamps added to the x264 codec, we establish a basis for detectability of events via packet timing. Laboratory experiments confirm that this event detection is possible in practice and repeatable. By collecting network traffic captures from over 100 Skype video calls we are able to see the impact of this information leakage under a variety of conditions.
28
Madurga, Martín-Serrano Juan Lucas. "A method for a small web site to add some sharing features." Thesis, Linköping University, Department of Science and Technology, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-11006.
Full textAbstract:
The aim of this diploma work is to compare and evaluate different methods to enable small web sites to make available videos which will be shared the users. Storage and bandwidth problems of small web sites are taken into account. The requirements of the system were defined as: configurable, feasible, easy use and easy to integrate. Existing solutions and different implementation alternatives are analyzed. With a tool based upon a CMS, using recordings residing on powerful dedicated video providers and with AJAX “technology”, the criteria are fulfilled. As part of the investigation, a prototype tool based upon TYPO3 has been implemented.
29
Head, Milena M. "User interface features, facilitating information access and decision making." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1998. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape10/PQDD_0007/NQ42743.pdf.
Full text
30
Head, Milena M. "User interface features : facilitating information access and decision making /." *McMaster only, 1997.
Find full text
31
Rudenko, Viktoria, Виктория Александровна Руденко, and Вікторія Олександравна Руденко. "Features of structure and regulation of the information market." Thesis, Видавництво СумДУ, 2007. http://essuir.sumdu.edu.ua/handle/123456789/8355.
Full textAbstract:
In conditions of an information society stresses of attention and the importance are displaced from traditional kinds of resources on information. Though information resources of a society exist basically so much, as long as a mankind, they were never considered as an economic category. Transition to market relations has caused occurrence of system of the markets within the limits of which the significant place should belong to the information market.
When you are citing the document, use the following link http://essuir.sumdu.edu.ua/handle/123456789/8355
32
Karphammar, Millie, and Jennifer Brettschneider. "eCRM features and customer loyalty : A qualitative study within the video streaming industry." Thesis, Umeå universitet, Företagsekonomi, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-185356.
Full textAbstract:
The video streaming industry has grown at a rapid speed during the past decade and has becomea trending topic in regard to technological advancements. Nowadays, there are manycompetitors in the market, and it is getting harder to stand out from the competition. Furthermore, the customers are demanding more in their choice of video streaming servicesand are expecting several features and functions in order to retain the service. Electronic Customer Relationship Management (eCRM) is a tool that has been used by providers of videostreaming services in order to improve long-term customer relationships. eCRM has beenresearched before as well as implemented by many companies. However, there are stillresearch gaps in relation to a potential impact that eCRM features have on customer loyalty, aswell as a managerial need to investigate these issues further. The purpose of this thesis is to develop deeper knowledge about how pre-, at- and postpurchase features of eCRM affect the customer loyalty in the video streaming industry. Thecontext of the study was the video streaming industry as it has increased majorly in popularityover the past years and there are many features to consider in the purchasing process. Therefore,we developed a conceptual model that was based on prior research to investigate the influenceof specific features on customer loyalty. The empirical data collection was conductedconsidering the conceptual model. This study was conducted by using a qualitative methodwith semi structured interviews, the respondents consisted of active users of a streaming serviceat the age between 18 to 34 years old. By analyzing the empirical data, we could determinefeatures of eCRM that affected and did not affect customer loyalty in our study. The findings showed that all the steps of the purchase process had features that affectedcustomer loyalty. The features of pre-purchase that we found relevant to customer loyalty inour study were captivating customers, which refers to the ability to attract customers' attention. The features of captivating customers are marketing, popularity, and recommendations, andout of these features, it was popularity and recommendation that we found affecting thecustomers loyalty. The features of the second step in the purchase process, at-purchase, that wefound affecting customer loyalty in our study were assortment, price, and convenience. Assortment refers to the content and supply of the service while the price refers to how muchthe service cost. Convenience is divided into four parts, the number of profiles, active users,devices that can use the service and the ability to stream offline, all these features exceptstreaming offline were found to have an effect on customer loyalty. Post-purchase refers to astage after the purchase has been made and, in our study, we found that the feature of clientcommunication has an effect on customer loyalty. Client communication is the communicationthat accrue between company and customer.
33
Price, Mathew. "Using colour features to classify objects and people in a video surveillance network." Master's thesis, University of Cape Town, 2004. http://hdl.handle.net/11427/5121.
Full textAbstract:
Includes bibliographical references (leaves 133-138).Visual tracking of humans has proved to be an extremely challenging task for computer vision systems. One idea towards a development of these systems is the incorporation of colour. Often colour appearance of a person can provide enough information to identify an object or person in the short-term. However, the imprecise nature of colour measurements typically encountered in image processing has limited their use. This thesis presents a system which uses colour appearances of objects and people for tracking across multiple camera views in a digital video surveillance network.
34
Salam, Sazilah. "VidIO : a model for personalized video information management." Thesis, University of Southampton, 1996. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.242411.
Full text
35
Barannik, Vlad, Y. Babenko, S. Shulgin, and M. Parkhomenko. "Video encoding to increase video availability in telecommunication systems." Thesis, Taras Shevchenko National University of Kyiv, 2020. https://openarchive.nure.ua/handle/document/16582.
Full textAbstract:
Article shows presence of the imbalance caused by insufficient level of productivity of modern and perspective information communication technologies concerning information intensity of bit streams. It is described how imbalance level reducing can be formed as a result of increasing of information processing technologies efficiency and that JPEG platform is the basic concept for construction of technologies of compression representation. Therefore it is proposed to provide further development of video processing methods using individual components of the JPEG platform for improving the integrity of information in terms of ensuring the required level of its availability.:
36
Meyn, Anselm Joseph. "Mobile Video Crawler : Implementing a video streaming Quality of Experience measurement system." Thesis, KTH, Skolan för informations- och kommunikationsteknik (ICT), 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-177326.
Full textAbstract:
The usage of mobile video streaming services is growing at a tremendous rate. Given the proliferation of Internet video streaming sites, there is growing interest in understanding the Quality of Experience (QoE) of using these services and the roles of the many factors that contribute to the QoE. QoE has a direct impact on customer retention, which means that poor QoE means loss of revenue for video service providers. The quality of experience of a video streaming service may be objectively evaluated with the use of metrics such as, the amount of buffering during video playback and the time before the video actually starts playing. Collecting this data for analysis on a large scale is quite challenging. In this thesis work we discuss the work done on developing a system for collection and analysis of these metrics. The major part of this work is the development of an mobile application that automates the process of playing a list of videos at configurable intervals and during playback of each video records events of interest such as system statistics, video player events and traffic traces. The application has been published and may be used from different locations to collect a rich data set for detailed analysis and modeling of QoE in mobile Internet video streaming.Användningen av mobila tjänster som utnyttjar video streaming växer i en snabb takt. I och med att antalet webbtjänster som utnyttjar video streaming ökar, finns det även ett växande intresse för att förstå Quality of Experience (QoE) för användningen av dessa tjänster, samt olika faktorer som inverkar på tjänstens QoE. QoE har en direkt inverkan på kundbevarande, vilket innebär att dålig QoE leder till förlorade intäkter för videotjänster. En videotjänsts kundupplevelse kan objektivt mätas med variabler som t.ex. antalet buffringspauser under tiden som videon spelas, samt tiden det tar för en video att börja spela. Att samla dessa data för analys på en större skala utgör en stor utmaning. I denna avhandling diskuterar vi arbetet som gjorts inom utvecklingen av ett system som samlar in och analyserar dessa variabler. Majoriteten av arbetet omfattar utvecklandet av en mobilapplikation som automatiskt spelar upp en lista av videon vid inställbara intervall, och under uppspelningen bandar in intressanta händelser så som statistik över systemet och nätverksanvändning, samt videospelarens händelser. Applikationen har blivit publicerad och kan användas från olika platser för att samla in en stor uppsättning data för detaljerad analys och modellering av QoE inom mobil Internet-video streaming.
37
Shah, Y. C. "Extraction of range information from stereo video images." Thesis, City University London, 1985. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.370923.
Full text
38
Akinola, Mobolaji. "Intelligent side information generation in distributed video coding." Thesis, Open University, 2015. http://oro.open.ac.uk/42625/.
Full textAbstract:
Distributed video coding (DVC) reverses the traditional coding paradigm of complex encoders allied with basic decoding to one where the computational cost is largely incurred by the decoder. This is attractive as the proven theoretical work of Wyner-Ziv (WZ) and Slepian-Wolf (SW) shows that the performance by such a system should be exactly the same as a conventional coder. Despite the solid theoretical foundations, current DVC qualitative and quantitative performance falls short of existing conventional coders and there remain crucial limitations. A key constraint governing DVC performance is the quality of side information (SI), a coarse representation of original video frames which are not available at the decoder. Techniques to generate SI have usually been based on linear motion compensated temporal interpolation (LMCTI), though these do not always produce satisfactory SI quality, especially in sequences exhibiting non-linear motion. This thesis presents an intelligent higher order piecewise trajectory temporal interpolation (HOPTTI) framework for SI generation with original contributions that afford better SI quality in comparison to existing LMCTI-based approaches. The major elements in this framework are: (i) a cubic trajectory interpolation algorithm model that significantly improves the accuracy of motion vector estimations; (ii) an adaptive overlapped block motion compensation (AOBMC) model which reduces both blocking and overlapping artefacts in the SI emanating from the block matching algorithm; (iii) the development of an empirical mode switching algorithm; and (iv) an intelligent switching mechanism to construct SI by automatically selecting the best macroblock from the intermediate SI generated by HOPTTI and AOBMC algorithms. Rigorous analysis and evaluation confirms that significant quantitative and perceptual improvements in SI quality are achieved with the new framework.
39
Rodrigues, Arturo Miguel Batista. "Coding of video with a single information plane." Master's thesis, Universidade de Aveiro, 2009. http://hdl.handle.net/10773/2103.
Full textAbstract:
Mestrado em Engenharia Electrónica e TelecomunicaçõesAs actuais normas para codificação de vídeo, tais como os MPEG2/4 ou H.263/4, foram desenvolvidas para codificação de vídeo com cor. A informação de cor é representada usando um espaço apropriado, como, por exemplo, o YCbCr. Estes espaços de cor são constituídos por três planos: um para a dominância (no exemplo dado, o Y) e dois para a informação de crominância (neste caso, o Cb e o Cr). Contudo, há aplicações onde a informação a codificar é composta apenas por um plano de informação que pode, por exemplo, representar níveis de cinzento em imagem médica, ou índices para tabelas de cores. A motivação desta tese prende-se com dois factos: a produção de imagens médicas em formato digital estar a crescer, impondo técnicas eficazes para o tratamento e a compressão de dados e, embora os modelos de cor indexada sejam há muito utilizados para representar imagens, não têm sido convenientemente explorados em vídeo. Com esta dissertação pretende-se investigar novas estratégias de compressão sem perdas que explorem a redundância entre imagens consecutivas que caracterizam estas modalidades de imagem. Portanto, ao longo do trabalho implementou-se dois codificadores de vídeo para um só plano de informação, baseados num modelo híbrido. Um deles utiliza codificação de Golomb e o outro codificação aritmética, estudando-se assim a eficácia de cada um, quer para a escala de cinzentos, quer para vídeos com tabela de cores indexadas. Adicionalmente, para vídeos de cor indexada, implementou-se um algoritmo de reordenação da tabela de cores, o que torna a codificação mais eficaz. ABSTRACT: The current standards for video encoding, such as MPEG2/4 or H.263/4, have been developed for encoding video with color. The color information is represented using an appropriate space, such as YCbCr. These color spaces are made of three planes: one for luminance (in the given example, the Y) and two for the chrominance information (in this case, the Cb and Cr). However, there are applications where the information lies in a single information plane that may, for example, represent shades of gray (medical imaging) or indexes to color tables (color indexed video). The motivation of this thesis is related with two points: the production of medical images in digital format has been growing, imposing efficient techniques for the treatment and compression of data and, although color indexed models have been used for a long time to represent images, it has not been adequately explored in video. With this thesis, we intended to investigate new strategies for lossless compression which exploits the redundancy between consecutive images that characterize these types of images. Therefore, during this work, it has been implemented two video encoders with one information plane, based on a hybrid model. One of them uses Golomb codes and the other arithmetic coding. It has been studied the efficiency of each one, both using gray scale and color indexed videos. In addition, for color indexed videos, it has been implemented a palette reordering algorithm, making the encoding more efficient.
40
McCarthy, Timothy Mortimer Mark. "Integrating aerial video with G.I.S." Thesis, Birkbeck (University of London), 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.324964.
Full text
41
Hu, Wei Shu. "Mining product features from online reviews." Thesis, University of Macau, 2010. http://umaclib3.umac.mo/record=b2148259.
Full text
42
Van, der Haar Dustin Terence. "Face recognition-based authentication and monitoring in video telecommunication systems." Thesis, 2012. http://hdl.handle.net/10210/5024.
Full textAbstract:
M.Sc. (Computer Science)A video conference is an interactive meeting between two or more locations, facilitated by simultaneous two-way video and audio transmissions. People in a video conference, also known as participants, join these video conferences for business and recreational purposes. In a typical video conference, we should properly identify and authenticate every participant in the video conference, if information discussed during the video conference is confidential. This prevents unauthorized and unwanted people from being part of the conference and exposing any confidential information during the video conference. Present existing video conferencing systems however, have problems in this area, resulting in some risks. These risks relate precisely to the lack of facilities to properly identify and authenticate participants, making it possible for unwanted/unauthorised participants to join the conference or masquerade as another participant. It is especially a problem, when facilitators or organisers are the only participants that know the authorised participants, or participants allowed in a video conference. In this dissertation, we review the risks that are present in video conferencing, and create a security system, (called BioVid) that mitigates the identification and authentication risks in video conferences. BioVid uses a Speeded-Up Robust Features or SURF-based face recognition approach, to identify and authenticate any participant in a video conference. BioVid continuously monitors the participants to check if masquerading has occurred and when it does detect an unauthorised participant, it informs the Service Provider. The Service Provider can then deal with the problem by either kicking the participant or asking the other participants to vote the unauthorised participant out of the video conference.
43
Ramalho, Pedro José Ascensão. "Feature Extraction and Object Classification in Video Sequences for Military Surveillance." Dissertação, 2019. https://hdl.handle.net/10216/122404.
Full textAbstract:
A detecção e reconhecimento de objectos requer um sistema de aprendizagem que possa identificar automaticamente um grupo de objectos, independentemente dos dados de entrada. Para que este tipo de identificação seja possível, este sistema precisa analisar previamente um grande grupo de dados para que possa memorizar pontos de interesse de diferentes objectos. Esta é a chamada fase de treino e é o primeiro passo em todos os processos de detecção e reconhecimento de machine learning.
Embora já existam muitos modelos que realizam a detecção e reconhecimento de um grande grupo de objectos, um dos objetivos deste projeto é especificar esta identificação para um grupo pequeno e especial de objetos. Isto torna-se possível usando transfer learning, que é um processo que usa o conhecimento adquirido, por um desses modelos, na resolução de um problema e aplica-o para solucionar uma questão diferente. Basicamente, tira proveito do resultado do processo de extração de características e utiliza-o para aprender a identificar outro tipo de objetos.
A extração de características é um grupo de processos com o objetivo de simplificar grandes grupos de dados, criando pequenos conjuntos de informações não redundantes. Esses pequenos grupos são mais fáceis de controlar, descrevem totalmente o conjunto de dados original e, ao usá-los, os recursos necessários para analisar um grande conjunto de dados são reduzidos.
Neste contexto, os dados a serem analisados serão capturados por uma câmara implementada num ponto estacionário ou num veículo. Quando se lida com a captura de informação visual é normal que um grande número de dados seja gerado. Por isso, é importante analisá-lo com eficiência e identificar informações que são relevantes.
Esta dissertação é realizada no âmbito militar, uma vez que os objectos a serem automaticamente identificados são tanques, armas, pessoas e veículos (carros e camiões), alcançando, assim, vigilância territorial.Object detection and recognition requires a learning system that can automatically identify a group of objects independently of the input data. To be able to perform this kind of identification, this system needs to previously analyze a large group of data, so it can memorize special features of different objects. This procedure it's called training and it's the first step in all the detection and recognition processes of machine learning. Although there are already many models that perform detection and recognition for a large group of objects, one of the goals of this project is to specify this identification into a small and special group of objects. This will be achieved by using transfer learning, that is a process that uses the knowledge gained by one of these models while solving one problem and applies it to a different one. Basically, it takes advantage of the feature extraction procedure outputs and use them to learn how to identify other kind of objects. Feature extraction is a group of processes with the goal of simplifying big groups of data by creating small sets of non-redundant information. These small groups are more manageable and can fully describe the original data set and, by using them, the resources necessary to analyse a large set of input data are decreased. In this context, the data to be analyzed will be captured by a camera implemented at a stationary point or in a vehicle. When dealing with the capture of visual information, it's normal that a large number of data is generated. So, it's important to analyze it efficiently and achieve relevant information identification. This dissertation focuses in military uses, therefore these operations are going to be used to automatically identify objects in the military field, that is, tanks, guns, people and vehicles (cars and trucks), achieving territorial surveillance.
44
Ramalho, Pedro José Ascensão. "Feature Extraction and Object Classification in Video Sequences for Military Surveillance." Master's thesis, 2019. https://hdl.handle.net/10216/122404.
Full textAbstract:
A detecção e reconhecimento de objectos requer um sistema de aprendizagem que possa identificar automaticamente um grupo de objectos, independentemente dos dados de entrada. Para que este tipo de identificação seja possível, este sistema precisa analisar previamente um grande grupo de dados para que possa memorizar pontos de interesse de diferentes objectos. Esta é a chamada fase de treino e é o primeiro passo em todos os processos de detecção e reconhecimento de machine learning.
Embora já existam muitos modelos que realizam a detecção e reconhecimento de um grande grupo de objectos, um dos objetivos deste projeto é especificar esta identificação para um grupo pequeno e especial de objetos. Isto torna-se possível usando transfer learning, que é um processo que usa o conhecimento adquirido, por um desses modelos, na resolução de um problema e aplica-o para solucionar uma questão diferente. Basicamente, tira proveito do resultado do processo de extração de características e utiliza-o para aprender a identificar outro tipo de objetos.
A extração de características é um grupo de processos com o objetivo de simplificar grandes grupos de dados, criando pequenos conjuntos de informações não redundantes. Esses pequenos grupos são mais fáceis de controlar, descrevem totalmente o conjunto de dados original e, ao usá-los, os recursos necessários para analisar um grande conjunto de dados são reduzidos.
Neste contexto, os dados a serem analisados serão capturados por uma câmara implementada num ponto estacionário ou num veículo. Quando se lida com a captura de informação visual é normal que um grande número de dados seja gerado. Por isso, é importante analisá-lo com eficiência e identificar informações que são relevantes.
Esta dissertação é realizada no âmbito militar, uma vez que os objectos a serem automaticamente identificados são tanques, armas, pessoas e veículos (carros e camiões), alcançando, assim, vigilância territorial.Object detection and recognition requires a learning system that can automatically identify a group of objects independently of the input data. To be able to perform this kind of identification, this system needs to previously analyze a large group of data, so it can memorize special features of different objects. This procedure it's called training and it's the first step in all the detection and recognition processes of machine learning. Although there are already many models that perform detection and recognition for a large group of objects, one of the goals of this project is to specify this identification into a small and special group of objects. This will be achieved by using transfer learning, that is a process that uses the knowledge gained by one of these models while solving one problem and applies it to a different one. Basically, it takes advantage of the feature extraction procedure outputs and use them to learn how to identify other kind of objects. Feature extraction is a group of processes with the goal of simplifying big groups of data by creating small sets of non-redundant information. These small groups are more manageable and can fully describe the original data set and, by using them, the resources necessary to analyse a large set of input data are decreased. In this context, the data to be analyzed will be captured by a camera implemented at a stationary point or in a vehicle. When dealing with the capture of visual information, it's normal that a large number of data is generated. So, it's important to analyze it efficiently and achieve relevant information identification. This dissertation focuses in military uses, therefore these operations are going to be used to automatically identify objects in the military field, that is, tanks, guns, people and vehicles (cars and trucks), achieving territorial surveillance.
45
Barbosa, Patrícia Margarida Silva de Castro Neves. "Human features detection in video surveillance." Master's thesis, 2016. http://hdl.handle.net/1822/46590.
Full textAbstract:
Dissertação de mestrado integrado em Engenharia Eletrónica Industrial e ComputadoresHuman activity recognition algorithms have been studied actively from decades using a sequence of 2D and 3D images from a video surveillance. This new surveillance solutions and the areas of image processing and analysis have been receiving special attention and interest from the scientific community. Thus, it became possible to witness the appearance of new video compression techniques, the transmission of audio and video in real-time, targeting identification and tracking objects in with complex environments. Traffic monitoring, automotive safety, people counting and activity recognition applications are examples. With the development of sensors, new opportunities arose to expand and advance this field. This dissertation presents an activity recognition system to recognize human motion. The system does not need optical markers or motion sensors. This human activity recognition system is divided in three stages: human segmentation, in an outside and inside environment; extraction of the human features; and classification models to detect the human actions. Therefore, the main objective in this work is to develop an algorithm to extract human features. This algorithm aims to develop a new representation and extraction method using a sequence of features in a skeleton silhouette. Mainly, the segmentation of humans is based on a previous work, centered on background subtraction. An algorithm is applied to convert the object captured in the video surveillance to a binary image using a skeleton algorithm. Afterwards, and based on the physical parameters of the human motion, it becomes possible to discover the principal features of the human skeleton, called physical features, head, hands and feet. The viability of using features detection in a human recognition system was tested and compared with other existing systems. The results point out that the system has good performance (8.96% of perfect match and the average rate was 68.65%). Nevertheless, in images where the features of the human body are covered, with umbrella or heavy coats for example, the system presents certain limitations. This process has a high execution speed and a low cost computational processing: average of 5910 µs with a standard deviation of 5650 µs. In the near future, classification models to detect the human actions will be included.
Algoritmos de reconhecimento de atividade humana foram estudados ativamente durante décadas, usando sequências de imagens em 2D e 3D de vídeo vigilância. Estas novas soluções de vídeo vigilância e as áreas de processamento e análise de imagens têm recebido especial atenção e interesse por parte da comunidade científica. Assim, tornou-se possível testemunhar a aparência de novas técnicas de compressão de vídeo, a transmissão de áudio e vídeo em tempo real, identificação de segmentação e rastreamento de objetos em ambientes complexos. Monitoramento de tráfego, segurança automóvel, contagem de pessoas e aplicações de reconhecimento de atividade são exemplos. Com o desenvolvimento de sensores, novas oportunidades surgiram para expandir e avançar neste campo. Esta dissertação apresenta um sistema de reconhecimento de atividade para reconhecer o movimento humano. O sistema não precisa de marcadores óticos ou sensores de movimento. Este sistema de reconhecimento de atividade humana divide-se em três fases: segmentação humana, num ambiente exterior e interior; Extração das características humanas; E modelos de classificação para detetar as ações humanas. Portanto, o objetivo principal deste trabalho trata-se de desenvolver um algoritmo para extrair características humanas. Este algoritmo tem como objetivo desenvolver uma nova representação e método de extração de características humanas, através do uso de uma silhueta em forma de esqueleto. A segmentação de seres humanos é baseada num trabalho anterior, centrado na subtração do plano de fundo. Um algoritmo é aplicado para converter o objeto capturado na vídeo vigilância, para uma imagem binária usando um algoritmo em forma de esqueleto. Posteriormente, e com base nos parâmetros físicos do movimento humano, torna-se possível descobrir as principais características do esqueleto humano, denominadas características físicas, cabeça, mãos e pés. A viabilidade do uso de deteção de características em um sistema de reconhecimento humano foi testada e comparada com outros sistemas. Os resultados indicam que o sistema tem bom desempenho (8.96% de correspondência exata e 68.65% de correspondência intermédia). No entanto, em imagens onde as características do corpo humano são cobertas, com guarda-chuva ou casacos pesados, por exemplo, o sistema apresenta certas limitações. Este processo tem uma alta velocidade de execução e um processamento computacional de baixo custo: média de 5910 μs com desvio padrão de 5650 μs. Num futuro próximo, serão incluídos modelos de classificação para detetar as ações humanas.
46
Tsou, Chih-Wei, and 鄒志偉. "Video Forgery Detection Using Combined Features." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/45728420382667617866.
Full textAbstract:
碩士國立中正大學
資訊工程所
97
We propose a new approach for locating forged regions in a video sequence without prior information. We also propose an approach which can detect different types of forgeries. In our test sequences, we use some forgeries such as video inpainting, splicing, resample, and dynamic texture synthesis. We utilize residual quantization error to detect forgeries and join color filter array, the correlation of noise residual to enhance our approach. These three features are good at some types of forgeries. Because these features have complementariness, we choose these features to detect different types of forgeries. Finally, we use decision tree to combine these features.
47
Lin, Yung-Chieh, and 林永傑. "Video Object Segmentation Using Flow-Thread Features." Thesis, 2000. http://ndltd.ncl.edu.tw/handle/39984296827681619309.
Full textAbstract:
碩士國立臺灣大學
資訊工程學研究所
88
The object-oriented functionality becomes one of the most important issues for the video processing system nowadays. Especially in the new generation of the video coding standards, MPEG-4, a video object in a scene is an entity that a user is allowed to access and manipulate. The instance of a video object at a given time can be given by a sub-image in a video frame with an arbitrary contour. The goal of the video object segmentation is to extract the instances of the video objects in an image sequence. In general, methods for video object segmentation assume that the individual video object has consistent spatiotemporal information. To utilize both the spatial and temporal information, the proposed method in this thesis combines the results of single image segmentation with the flow-thread features. Here, a flow-thread is a series of pixels obtained by tracing the motion vectors along the image sequence. This thesis is organized into three parts: (1) the segmentation of single images, (2) the flow-thread construction, and (3) the flow-thread analysis and classification. In the segmentation of single images, we will introduce a popular morphological method, and compare its two algorithms using different approaches. In the flow-thread construction, a fast algorithm is used to refine the pixel-level motion vectors to the subpixel precision. This algorithm is based on the block matching and bilinear interpolation. After the motion vectors are refined, the flow-threads can be constructed by tracing the motion vectors. In the flow-thread analysis, the discrete Fourier transform and discrete wavelet transform are used for extracting the features of flow-threads. Finally, we use the conventional pattern recognition techniques to segment the scene into VOs based on the flow-thread features and regions obtained in the single image segmentation. Our method was used to segment some MPEG-4 test sequence, and the segmentation results are promising.
48
Lin, Chih-long, and 林志隆. "Content-based Video Retrieval with Multi Features." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/ed84t6.
Full textAbstract:
碩士國立臺灣科技大學
電機工程系
102
With the advance of multimedia codec technology and communications, multimedia communications become one of the major information media with the aides of internet prevalence. Under this circumstance, image and video data over the Internet contribute to the sea of media and how to search user desired media contents from the sea of media becomes important. Content-Based Video Retrieval (CBVR) methods have been proposed to search user interested video clips, precisely and quickly. Among these researches, extracting image features for similarity measurement is widely adopted. However, adopting only one kind of feature to describe video contents cannot provide satisfactory retrieval results. In general, more than one kind of image/video features are extracted to for efficient video retrieval. How to efficiently integrate different kinds of image/video features is critical and challenging in improving the video retrieval performance. In this thesis, we proposed to integrate color, texture and SIFT-BOW (Bag of Word) image features to describe one video clip. These three features not only can describe the global image feature, but also local region ones. In our experiments, the color histogram difference is used to measure similarity for video scene cut. These video scene cuts, video clips, are used as the basic media unit for description and retrieval. The average of image features within one media unit is used as the representative feature for the video clip. To perform retrieval, the feature of one query image/video is extracted and its similarity to each representative feature of one video clip in a database is calculated to perform similarity ranking. For comparisons, the video retrieval performance that adopts only one feature is implemented. In addition, the one proposed by Y. Deng [10] that adopts more than one feature for video retrieval is also carried out for comparisons. Experiments showed that the proposed CBVR method outperforms the previous method by 38.7% in the PR rate. Performing CBVR by multiple features also improves on the PR performance as compared to retrieval by single feature.
49
Wu, Jui-Chen, and 吳瑞珍. "Salient Features Extraction for Video Content Analysis." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/30681624290573307145.
Full textAbstract:
博士元智大學
電機工程學系
97
Multimedia can be widely used due to the progress of science and technology. An automatic object detection and analysis system is necessary that we can ability transmits, store and retrieve for video data. To achieve these goals, there have been many approaches proposed for detecting object for a plan or visual median. Hence, having a detailed description of video content analysis can provide rich information for user. In this thesis, we will propose two novel salient features extraction schemes for text detection and recognition in images or video sequences, vehicle orientation analysis and vehicle retrieval from image databases. First, the morphology-based scheme can be used to find out high contrast region with their background. The method is invariant under different lighting, scaling, and viewing conditions. As a result of text often having high contrast with their background, all possible candidate regions will be extracted. Finally, the geometric properties can be used to detect text line from images. After extracting, we will recognize license plate from video sequences. Moreover, to fast and effectively analyze vehicles from image databases, we proposed the “eigen” color extraction scheme to detect possible vehicle regions from cluttered images. The model can efficiently separate foreground pixels from the cluttered images even under different lighting conditions. After extracting candidates regions, we will define some descriptors to achieve vehicle orientation analysis and vehicle retrieval system. Experimental results reveal the superior performances in text extraction, license plate recognition, vehicle orientation analysis, and vehicle retrieval.
50
Chen, Wei-Chung, and 陳韋均. "Rushes Video Summarization by Audio-filtering Visual Features." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/43004645505593306250.
Full textAbstract:
碩士國立雲林科技大學
資訊工程系碩士班
100
In this paper, we propose a video summarization system for analyzing basketball game videos. In contrast to previous video analysis technologies employing only visual and motion features to do video filtering, we add audio features to do video summarization in the system. First, we extract replay highlights by special effect detection. Next, we filter landscape shots using color range pixel and fast motion activity. Then, the corresponding audio features extracted from these landscape shots are used to identify landscape shot highlights by an SVM. Finally, we integrate the replay highlights and landscape shot highlights to complete the video summarization. From the experimental results, we find that the accuracy on the special effect detection, landscape shot extraction, and landscape shot highlight detection is very high. Thus, the final video summarization has high recall values on highlight extraction.