Дисертації з теми "Computer vision algorithm"
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Anani-Manyo, Nina K. "Computer Vision and Building Envelopes." Kent State University / OhioLINK, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=kent1619539038754026.
Повний текст джерелаMac, Aodha O. "Supervised algorithm selection for flow and other computer vision problems." Thesis, University College London (University of London), 2014. http://discovery.ucl.ac.uk/1426968/.
Повний текст джерелаZakaria, Marwan F. "An automated vision system using a fast 2-dimensional moment invariants algorithm /." Thesis, McGill University, 1987. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=66244.
Повний текст джерелаZhang, Lichang. "Non-invasive detection algorithm of thermal comfort based on computer vision." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-241082.
Повний текст джерелаSlöseriet med att bygga energiförbrukningen är en stor utmaning i världen. Ochdetektering av mänsklig termisk komfort i realtid är ett effektivt sätt att lösaproblemet. Som nämns i namn betyder det att detektera människans komfortnivå i realtid och icke-invasivt. På grund av de olika faktorerna som individuell skillnad i termisk komfort, är emellertid faktorer som är relaterade till klimat (temperatur, luftfuktighet, belysning etc.) det fortfarande en lång väg att implementera denna strategi i verkligheten. Från ett annat perspektiv kan nuvarande system för uppvärmning, ventilation och luftkonditionering inte tillhandahålla flexibla interaktionskanaler för att anpassa atmosfären och naturligtvis misslyckas till nöjda krav från användarna. Alla indikerar nödvändigheten av att utveckla en detekteringsmetod för mänsklig termisk komfort. I detta dokument föreslås en ickeinvasion detekteringsmetod mot mänsklig termisk komfort från två perspektiv: makro mänskliga hållningar och hudtexturer. I hållningspartiet används OpenPose för att analysera positionskoordinaterna för kroppens huvudpunkter i bilder, till exempel armbåge, knä och höftben osv. Och resultaten av analysen skulle tolkas från termen av termisk komfort. I hudtexturer används djupt neuralt nätverk för att förutse temperaturen på mänskliga skinn via bilder. Baserat på Fangers teorin om värmekomfort är resultaten av båda delarna tillfredsställande: subjektens hållningar kan fångas och tolkas till olika värmekomfortnivåer: varm, kall och komfort. Och det absoluta felet av prediktering från neuronnätverket är mindre än 0,125 grader Celsius, vilket är utrustningsfelet hos termometern som används vid datainsamling. Med lösningar i detta papper är det lovande att detektera användarens värmekomfortnivå fritt från invändningar och hudtexturer. Slutligen diskuteras slutsatserna och detframtida arbetet i sista kapitlet.
Anderson, Travis M. "Motion detection algorithm based on the common housefly eye." Laramie, Wyo. : University of Wyoming, 2007. http://proquest.umi.com/pqdweb?did=1400965531&sid=1&Fmt=2&clientId=18949&RQT=309&VName=PQD.
Повний текст джерелаChavez, Aaron J. "A fast interest point detection algorithm." Thesis, Manhattan, Kan. : Kansas State University, 2008. http://hdl.handle.net/2097/538.
Повний текст джерелаBergendahl, Jason Robert. "A computationally efficient stereo vision algorithm for adaptive cruise control." Thesis, Massachusetts Institute of Technology, 1997. http://hdl.handle.net/1721.1/43389.
Повний текст джерелаIncludes bibliographical references (p. 55-56).
by Jason Robert Bergendahl.
M.S.
Ng, Brian Walter. "Wavelet based image texture segementation using a modified K-means algorithm." Title page, table of contents and abstract only, 2003. http://web4.library.adelaide.edu.au/theses/09PH/09phn5759.pdf.
Повний текст джерелаRamswamy, Lakshmy. "PARZSweep a novel parallel algorithm for volume rendering of regular datasets /." Master's thesis, Mississippi State : Mississippi State University, 2003. http://library.msstate.edu/etd/show.asp?etd=etd-04012003-140443.
Повний текст джерелаJohnson, Amanda R. "A pose estimation algorithm based on points to regions correspondence using multiple viewpoints." Laramie, Wyo. : University of Wyoming, 2008. http://proquest.umi.com/pqdweb?did=1798480891&sid=1&Fmt=2&clientId=18949&RQT=309&VName=PQD.
Повний текст джерелаSchwambach, Vítor. "Methods and tools for rapid and efficient parallel implementation of computer vision algorithms on embedded multiprocessors." Thesis, Université Grenoble Alpes (ComUE), 2016. http://www.theses.fr/2016GREAM022/document.
Повний текст джерелаEmbedded computer vision applications demand high system computational power and constitute one of the key drivers for application-specific multi- and many-core systems. A number of early system design choices can impact the system’s parallel performance – among which the parallel granularity, the number of processors and the balance between computation and communication. Their impact in the final system performance is difficult to assess in early design stages and there is a lack for tools that support designers in this task. The contributions of this thesis consist in two methods and associated tools that facilitate the selection of embedded multiprocessor’s architectural parameters and computer vision application parallelization strategies. The first consists of a Design Space Exploration (DSE) methodology that relies on Parana, a fast and accurate parallel performance estimation tool. Parana enables the evaluation of what-if parallelization scenarios and can determine their maximum achievable performance limits. The second contribution consists of a method for optimal 2D image tile sizing using constraint programming within the Tilana tool. The proposed method integrates non-linear DMA data transfer times and parallel scheduling overheads for increased accuracy
Turk, Matthew Robert. "A homography-based multiple-camera person-tracking algorithm /." Online version of thesis, 2008. http://hdl.handle.net/1850/7853.
Повний текст джерелаKhekare, Pranav Prakash. "Application of Computer Vision algorithm and Deep learning for roundabout capacity evaluation using UAV aerial imagery and videos." University of Cincinnati / OhioLINK, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1613748930108492.
Повний текст джерелаGhosh, Payel. "Medical Image Segmentation Using a Genetic Algorithm." PDXScholar, 2010. https://pdxscholar.library.pdx.edu/open_access_etds/25.
Повний текст джерелаBae, Sung Eun. "Sequential and Parallel Algorithms for the Generalized Maximum Subarray Problem." Thesis, University of Canterbury. Computer Science and Software Engineering, 2007. http://hdl.handle.net/10092/1202.
Повний текст джерелаManfredsson, Johan. "Evaluation Tool for a Road Surface Algorithm." Thesis, Linköpings universitet, Datorseende, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-138936.
Повний текст джерелаKemp, Neal. "Content-Based Image Retrieval for Tattoos: An Analysis and Comparison of Keypoint Detection Algorithms." Scholarship @ Claremont, 2013. http://scholarship.claremont.edu/cmc_theses/784.
Повний текст джерелаVidas, Dario. "Performance Evaluation of Stereo Reconstruction Algorithms on NIR Images." Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-191148.
Повний текст джерелаLakshman, Prabhashankar. "Parallel implementation of the split and merge algorithm on the hypercube machine." Ohio : Ohio University, 1989. http://www.ohiolink.edu/etd/view.cgi?ohiou1182440993.
Повний текст джерелаAldrovandi, Lorenzo. "Depth estimation algorithm for light field data." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2018.
Знайти повний текст джерелаALAHMAD, MOUHAMAD. "Developpement de methodes de vision par ordinateur : extraction de primitives geometriques." Université Louis Pasteur (Strasbourg) (1971-2008), 1986. http://www.theses.fr/1986STR13192.
Повний текст джерелаLef, Annette. "CAD-Based Pose Estimation - Algorithm Investigation." Thesis, Linköpings universitet, Datorseende, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-157776.
Повний текст джерелаBotterill, Tom. "Visual navigation for mobile robots using the Bag-of-Words algorithm." Thesis, University of Canterbury. Computer Science and Software Engineering, 2011. http://hdl.handle.net/10092/5511.
Повний текст джерелаLefebvre, Thomas. "Exploration architecturale pour la conception d'un système sur puce de vision robotique, adéquation algorithme-architecture d'un système embarqué temps-réel." Phd thesis, Université de Cergy Pontoise, 2012. http://tel.archives-ouvertes.fr/tel-00782081.
Повний текст джерелаBortolot, Zachary Jared. "An Adaptive Computer Vision Technique for Estimating the Biomass and Density of Loblolly Pine Plantations using Digital Orthophotography and LiDAR Imagery." Diss., Virginia Tech, 2004. http://hdl.handle.net/10919/27454.
Повний текст джерелаPh. D.
Ivarsson, Adam. "Expediting Gathering and Labeling of Data from Zebrafish Models of Tumor Progression and Metastasis Using Bespoke Software." Thesis, Linköpings universitet, Institutionen för datavetenskap, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-148691.
Повний текст джерелаTippetts, Beau J. "Real-Time Implementation of Vision Algorithm for Control, Stabilization, and Target Tracking for a Hovering Micro-UAV." BYU ScholarsArchive, 2008. https://scholarsarchive.byu.edu/etd/1418.
Повний текст джерелаGuidi, Gianluca. "A new algorithm for estimating pedestrian flows during massive touristic events, optimized for an existing camera setup." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2017. http://amslaurea.unibo.it/14552/.
Повний текст джерелаBOUYAKHF, EL-HOUSSINE. "Description et interpretation d'images pour la vision en robotique : reconnaissance d'objets partiellement observes." Toulouse 3, 1988. http://www.theses.fr/1988TOU30016.
Повний текст джерелаDatari, Srinivasa R. "Hypercube machine implementation of a 2-D FFT algorithm for object recognition." Ohio : Ohio University, 1989. http://www.ohiolink.edu/etd/view.cgi?ohiou1182434398.
Повний текст джерелаKhajo, Gabriel. "Region Proposal Based Object Detectors Integrated With an Extended Kalman Filter for a Robust Detect-Tracking Algorithm." Thesis, Karlstads universitet, Fakulteten för hälsa, natur- och teknikvetenskap (from 2013), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kau:diva-72698.
Повний текст джерелаТарановський, Антон Володимирович, Антон Владимирович Тарановский, Anton Volodymyrovych Taranovskyi, Сергій Олександрович Петров, Сергей Александрович Петров та Serhii Oleksandrovych Petrov. "Визначення оптимальних параметрів вхідного зображення на характеристики розпізнавання з використанням алгоритму Віола-Джонса". Thesis, Видавництво СумДУ, 2013. http://essuir.sumdu.edu.ua/handle/123456789/42602.
Повний текст джерелаBodily, John M. "An Optical Flow Implementation Comparison Study." Diss., CLICK HERE for online access, 2009. http://contentdm.lib.byu.edu/ETD/image/etd2818.pdf.
Повний текст джерелаViloria, John A. (John Alexander) 1978. "Optimizing clustering algorithms for computer vision." Thesis, Massachusetts Institute of Technology, 2001. http://hdl.handle.net/1721.1/86847.
Повний текст джерелаAlbertazzi, Riccardo. "Sistema di visione stereo su architettura ZYNQ." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2016. http://amslaurea.unibo.it/11310/.
Повний текст джерелаGultekin, Gokhan Koray. "An Fpga Based High Performance Optical Flow Hardware Design For Autonomous Mobile Robotic Platforms." Master's thesis, METU, 2010. http://etd.lib.metu.edu.tr/upload/12612483/index.pdf.
Повний текст джерелаSchunck is selected for this implementation. The complete hardware design of the proposed system is described in details. We also discuss the design alternatives and the selected approaches together with a discussion of the selection procedure. We present the performance analysis of the proposed hardware in terms of computation speed, power consumption and accuracy. The designed hardware is tested with some of the available test sequences that are frequently used for performance evaluations of the optical flow techniques in literature. The proposed hardware is capable of computing optical flow vector field on 256x256 pixels images in 3.89ms which corresponds to a processing speed of 257 fps. The results obtained from FPGA implementation are compared with a floating-point implementation of the same algorithm realized on a PC hardware. The obtained results show that the hardware implementation achieved a superior performance in terms of speed, power consumption and compactness while there is minimal loss of accuracy due to the fixed point implementation.
Javadi, Mohammad Saleh. "Computer Vision Algorithms for Intelligent Transportation Systems Applications." Licentiate thesis, Blekinge Tekniska Högskola, Institutionen för matematik och naturvetenskap, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-17166.
Повний текст джерелаLim, Choon Kee. "Hypercube machine implementation of low-level vision algorithms." Ohio : Ohio University, 1989. http://www.ohiolink.edu/etd/view.cgi?ohiou1182864143.
Повний текст джерелаCarletti, Angelo. "Development of a machine learning algorithm for the automatic analysis of microscopy images in an in-vitro diagnostic platform." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2021.
Знайти повний текст джерелаEl, Gheche Mireille. "Proximal methods for convex minimization of Phi-divergences : application to computer vision." Thesis, Paris Est, 2014. http://www.theses.fr/2014PEST1018/document.
Повний текст джерелаConvex optimization aims at searching for the minimum of a convex function over a convex set. While the theory of convex optimization has been largely explored for about a century, several related developments have stimulated a new interest in the topic. The first one is the emergence of efficient optimization algorithms, such as proximal methods, which allow one to easily solve large-size nonsmooth convex problems in a parallel manner. The second development is the discovery of the fact that convex optimization problems are more ubiquitous in practice than was thought previously. In this thesis, we address two different problems within the framework of convex optimization. The first one is an application to computer stereo vision, where the goal is to recover the depth information of a scene from a pair of images taken from the left and right positions. The second one is the proposition of new mathematical tools to deal with convex optimization problems involving information measures, where the objective is to minimize the divergence between two statistical objects such as random variables or probability distributions. We propose a convex approach to address the problem of dense disparity estimation under varying illumination conditions. A convex energy function is derived for jointly estimating the disparity and the illumination variation. The resulting problem is tackled in a set theoretic framework and solved using proximal tools. It is worth emphasizing the ability of this method to process multicomponent images under illumination variation. The conducted experiments indicate that this approach can effectively deal with the local illumination changes and yields better results compared with existing methods. We then extend the previous approach to the problem of multi-view disparity estimation. Rather than estimating a single depth map, we estimate a sequence of disparity maps, one for each input image. We address this problem by adopting a discrete reformulation that can be efficiently solved through a convex relaxation. This approach offers the advantage of handling both convex and nonconvex similarity measures within the same framework. We have shown that the additional complexity required by the application of our method to the multi-view case is small with respect to the stereo case. Finally, we have proposed a novel approach to handle a broad class of statistical distances, called $varphi$-divergences, within the framework of proximal algorithms. In particular, we have developed the expression of the proximity operators of several $varphi$-divergences, such as Kulback-Leibler, Jeffrey-Kulback, Hellinger, Chi-Square, I$_{alpha}$, and Renyi divergences. This allows proximal algorithms to deal with problems involving such divergences, thus overcoming the limitations of current state-of-the-art approaches for similar problems. The proposed approach is validated in two different contexts. The first is an application to image restoration that illustrates how to employ divergences as a regularization term, while the second is an application to image registration that employs divergences as a data fidelity term
Orloski, Andrey. "PROCEDIMENTO PARA AUTOLOCALIZAÇÃO DE ROBÔS EM CASAS DE VEGETAÇÃO UTILIZANDO DESCRITORES SURF: Implementação Sequencial e Paralela." UNIVERSIDADE ESTADUAL DE PONTA GROSSA, 2015. http://tede2.uepg.br/jspui/handle/prefix/130.
Повний текст джерелаThis paper describes a procedure for self-localization of mobile and autonomous agrobots in greenhouses, that is, the determination of the robot's position relative to a coordinate system,using procedures and computational resources. The proposed procedure uses computer vision techniques to recognize markers objects in the greenhouse and, from them, estimate the coordinate of the robot in a parallel plane to the surface of the stove. The detection of the presence of markers in the scene is performed using the SURF algorithm. To enable the estimation of coordinates, based on data contained in a single image, the method of Rahman et al. (2008), which consists in etermining the distance between a camera and a marker object has been extended to allow the coordinate calculation. The performance of the procedure was evaluated in three experiments. In the first experiment, the objective was to verify, in the laboratory, the influence of image resolution on accuracy. The results indicate that by reducing the image resolution, the range of the process is impaired for the recognition of the markers. These results also show that by reducing the resolution, the error in estimating the coordinates relative to the distance between the camera and the marker increases. The second experiment ran a test that evaluates the computational performance of the SURF algorithm, in terms of computing time, in the image processing. This is important because agrobots usually need to perform tasks that require the processing power in real time. The results of this test indicate that the efficiency of the procedure drops with the increase of image resolution. A second test compared the processing time of two implementations of the algorithm. One explores a sequential version of the SURF algorithm and another uses a parallel implementation. The results of this test suggest that the parallel implementation is more efficient in all tested resolutions, with an almost constant proportionate improvement.The third experiment was performed in a greenhouse to evaluate the performance of the proposed procedure in the environment for which it was designed. Field results were similar to the laboratory, but indicate that lighting variations require parameter settings of the SURF algorithm.
Este trabalho descreve um procedimento para autolocalização de agrobots móveis e autônomos em casas de vegetação. Isto é, a determinação da posição do robô em relação a um sistema de coordenadas, usando procedimentos e recursos computacionais. O procedimento proposto emprega técnicas de visão computacional para reconhecer objetos marcadores na casa de vegetação e, a partir deles, estimar a coordenada do robô em um plano paralelo a superfície da estufa. A detecção da presença dos marcadores na cena é realizada através do algoritmo SURF. Para viabilizar a estimativa das coordenadas, a partir de dados contidos em uma única imagem, o método de Rahman et al. (2008), que consiste em determinar a distância entre uma câmera e um objeto marcador, foi estendido para permitir o cômputo de coordenadas. O desempenho do procedimento proposto foi avaliado em três experimentos. No primeiro experimento, o objetivo foi verificar, em laboratório, a influência da resolução da imagem sobre a precisão. Os resultados indicam que, ao reduzir a resolução da imagem, o alcance do procedimento é prejudicado para reconhecimento dos marcadores. Estes resultados também mostram que, ao reduzir a resolução, o erro na estimativa das coordenadas em relação à distância entre a câmera e o marcador aumenta. O segundo experimento executou um teste que avalia o desempenho computacional do algoritmo SURF, em termos de tempo de computação, no processamento das imagens. Isto é importante pois agrobots usualmente precisam executar tarefas que demandam capacidade de processamento em tempo real. Os resultados deste teste indicam que a eficiência do procedimento cai com o aumento da resolução da imagem. Um segundo teste comparou o tempo de processamento de duas implementações do algoritmo. Uma que explora uma versão sequencial do algoritmo SURF e outra que usa uma implementação paralela. Os resultados deste teste sugerem que a implementação paralela foi mais eficiente em todas as resoluções testadas, apresentando uma melhora proporcional quase constante. O terceiro experimento foi realizado em uma casa de vegetação com objetivo de avaliar o desempenho do procedimento proposto no ambiente para o qual foi projetado. Os resultados de campo se mostraram semelhantes aos do laboratório, mas indicam que variações de iluminação exigem ajustes de parâmetros do algoritmo SURF.
Boisard, Olivier. "Optimization and implementation of bio-inspired feature extraction frameworks for visual object recognition." Thesis, Dijon, 2016. http://www.theses.fr/2016DIJOS016/document.
Повний текст джерелаIndustry has growing needs for so-called “intelligent systems”, capable of not only ac-quire data, but also to analyse it and to make decisions accordingly. Such systems areparticularly useful for video-surveillance, in which case alarms must be raised in case ofan intrusion. For cost saving and power consumption reasons, it is better to perform thatprocess as close to the sensor as possible. To address that issue, a promising approach isto use bio-inspired frameworks, which consist in applying computational biology modelsto industrial applications. The work carried out during that thesis consisted in select-ing bio-inspired feature extraction frameworks, and to optimize them with the aim toimplement them on a dedicated hardware platform, for computer vision applications.First, we propose a generic algorithm, which may be used in several use case scenarios,having an acceptable complexity and a low memory print. Then, we proposed opti-mizations for a more global framework, based on precision degradation in computations,hence easing up its implementation on embedded systems. Results suggest that whilethe framework we developed may not be as accurate as the state of the art, it is moregeneric. Furthermore, the optimizations we proposed for the more complex frameworkare fully compatible with other optimizations from the literature, and provide encourag-ing perspective for future developments. Finally, both contributions have a scope thatgoes beyond the sole frameworks that we studied, and may be used in other, more widelyused frameworks as well
Habe, Hitoshi. "Geometric information processing methods for elaborating computer vision algorithms." 京都大学 (Kyoto University), 2006. http://hdl.handle.net/2433/136028.
Повний текст джерелаNilsson, Mattias. "Evaluation of Computer Vision Algorithms Optimized for Embedded GPU:s." Thesis, Linköpings universitet, Datorseende, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-112575.
Повний текст джерелаApewokin, Senyo. "Efficiently mapping high-performance early vision algorithms onto multicore embedded platforms." Diss., Atlanta, Ga. : Georgia Institute of Technology, 2009. http://hdl.handle.net/1853/28256.
Повний текст джерелаCommittee Chair: Wills, Scott; Committee Co-Chair: Wills, Linda; Committee Member: Bader, David; Committee Member: Davis, Jeff; Committee Member: Hamblen, James; Committee Member: Lanterman, Aaron.
Головацький, Ігор Володимирович. "Інтелектуальна система розпізнавання елементів дорожнього руху". Master's thesis, КПІ ім. Ігоря Сікорського, 2019. https://ela.kpi.ua/handle/123456789/31808.
Повний текст джерелаExamines the problem of recognition of traffic elements in the video stream, analyzes the existing problems and complexities in the existing methods of recognition of the elements and compares their characteristics of accuracy and speed, advantages and disadvantages. An intelligent system for recognizing traffic elements is using machine learning algorithms and neural networks. The system can be used in video recorders and passive vehicle security systems. In general, the paper addresses the purpose and feasibility of using a neural network and presents the software implementation of the system using the C# programming language and the Accord.NET library. The main requirements of which are: acceptable recognition accuracy, the ability to use video stream as input, found elements should be intuitive highlighted among other elements and simplicity in configuring. Special attention was paid to the local results of the experiments, which give an idea of the characteristics of the proposed system. Explanatory note size – 81 pages, contains 23 illustrations, 28 tables, 6 applications.
Vivet, Tañà Marc. "Fast Computer Vision Algorithms applied to Motion Detection and Mosaicing." Doctoral thesis, Universitat Autònoma de Barcelona, 2013. http://hdl.handle.net/10803/125980.
Повний текст джерелаThis thesis is focused on motion detection and its use for the summarization of video scenes in mosaic images. While mosaicing with pivoting cameras is a well-known topic, this is not the case with full motion cameras. The first step is to align all the images into a single coordinate system. This process, named image alignment, comes from the estimation of the transform that projects every video image into this common coordinate system. The mosaic image is generated assigning to each point some value derived from the information conveyed for the different images with information about that point. Motion and Mosaicing are deeply related. The thesis is organized in six chapters. After an introduction to the perceptual aspects of motion in a video sequence and exposing the plan of the thesis, the second chapter deals with the problem of detecting motion using static cameras. To this end, an extensive description of the main background subtraction algorithms in the literature is presented. The original background subtraction algorithm developed in the thesis is presented. This algorithm combines different visual cues and uses a probabilistic graphical model to provide spatio-temporal consistency to the background model. This model represents each pixel as a random variable with two states, background and foreground. Then, Markov Random Fields (MRF) is used to describe the correlation between neighbouring pixels in the space-time volume. In addition, a general framework to combine different motion related information sources is presented in order to increase the accuracy of the motion mask. The next step is to face the problem of detecting motion when the camera is not static, which is analysed in the chapter 3. In particular, the case with no parallax is considered. This is a common case as PTZ cameras or aerial perspectives do not produce motion parallax. It is proposed to compensate for 2D affine transformations caused by the camera by using Multiple Kernel Tracking, assuming that the major part of the frame belongs to the background. The first step is to introduce Multiple Kernel Tracking describing how it can be formulated for this particular purpose. Then the generation of the background mosaic is defined and it adaptability over time. Chapter 4 presents a new frame alignment algorithm, the Direct Local Indirect global (DLIG), which compensates the 2D motion using a projective transformation. The key idea of the DLIG alignment is to divide the frame alignment problem into the problem of registering a set of spatially related image patches. The registration is iteratively computed by sequentially imposing a good local match and global spatial coherence. The patch registration is performed using a tracking algorithm, so a very efficient local matching can be achieved. The algorithm uses the patch-based registration to obtain multiframe registration, using the mosaic coordinates to relate the current frame to patches from different frames that partially share the current field of view. Multiframe registration prevents the error accumulation problem, one of the most important problems in mosaicing. It is also show how to embed a Kernel Tracking algorithm in order to obtain a precise and efficient mosaicing algorithm. The chapter 5 moves to the problem of generating mosaics when the recorded scene contains motion parallax. The developed solution proposes to align the video sequence in a space-time volume based on efficient feature tracking using a Kernel Tracking algorithm. Computation is fast and, as the motion, is computed only for a few regions of the image, yet still gives accurate 3D motion. This computation is faster and more accurate than the previous work that is based on a direct alignment method. The synthesis of the mosaic image is faced with the novel Barcode Blending , a new approach for using pyramid blending in video mosaics, which is very efficient. Barcode Blending overcomes the complexity of building pyramids for multiple narrow strips, combining all strips in a single blending step. This thesis finishes with the conclusions and future work in chapter 6.
Avdiu, Blerta. "Matching Feature Points in 3D World." Thesis, Tekniska Högskolan, Högskolan i Jönköping, JTH, Data- och elektroteknik, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-23049.
Повний текст джерелаKim, Kyungnam. "Algorithms and evaluation for object detection and tracking in computer vision." College Park, Md. : University of Maryland, 2005. http://hdl.handle.net/1903/2925.
Повний текст джерелаThesis research directed by: Computer Science. Title from t.p. of PDF. Includes bibliographical references. Published by UMI Dissertation Services, Ann Arbor, Mich. Also available in paper.
Gu, Jian. "Development of computer vision algorithms using J2ME for mobile phone applications." Thesis, University of Canterbury. Computer Science and Software Engineering, 2009. http://hdl.handle.net/10092/2683.
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