Relevant bibliographies by topics / Intelligent surveillance system

Academic literature on the topic 'Intelligent surveillance system'

Author: Grafiati
Published: 10 March 2023
Last updated: 11 March 2023

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Journal articles on the topic "Intelligent surveillance system"

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Praveen, Dabbara. "Intelligent Video Surveillance System." International Journal for Research in Applied Science and Engineering Technology 9, no. VIII (August 15, 2021): 741–43. http://dx.doi.org/10.22214/ijraset.2021.37399.

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Intelligent video recognition with in-depth learning concept will create a self-paced video analytics program. CCTV cameras are used in all areas where safety is paramount. Manual monitoring seems tedious and time-consuming. Security can be defined by different words in different contexts such as identity theft, violence, explosions etc. Security monitoring is a tedious and time-consuming task. In this project we will analyse video feeds in real time and identify any unusual items such as violence or theft. The concept of in-depth learning simulates the functioning of the human brain in processing data for use in acquisition, speech recognition, decision making, etc. This will depend without human guidance, from unstructured and unlabelled data.
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Sanoob, A. H., J. Roselin, and P. Latha. "Smartphone Enabled Intelligent Surveillance System." IEEE Sensors Journal 16, no. 5 (March 2016): 1361–67. http://dx.doi.org/10.1109/jsen.2015.2501407.

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Liu, Hong Tao. "Design of Low-Cost Airport Boundary Intelligent Video Surveillance System." Applied Mechanics and Materials 443 (October 2013): 228–32. http://dx.doi.org/10.4028/www.scientific.net/amm.443.228.

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The existing Airport boundary intelligent video surveillance system is complicated to construct and costs a lot. This paper presents a design of economical Airport boundary intelligent video surveillance system according to the principle of optimization system and the resources share, combined the motion detection technology of NVR with intelligence video analyze equipment. The design can greatly decrease the false alarm rate and reduced the number of intelligence video analysis equipment. Therefor, it has higher application value and practical significance.
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Rghioui, Amine, Jaime Lloret, Mohamed Harane, and Abdelmajid Oumnad. "A Smart Glucose Monitoring System for Diabetic Patient." Electronics 9, no. 4 (April 22, 2020): 678. http://dx.doi.org/10.3390/electronics9040678.

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Diabetic patients need ongoing surveillance, but this involves high costs for the government and family. The combined use of information and communication technologies (ICTs), artificial intelligence and smart devices can reduce these costs, helping the diabetic patient. This paper presents an intelligent architecture for the surveillance of diabetic disease that will allow physicians to remotely monitor the health of their patients through sensors integrated into smartphones and smart portable devices. The proposed architecture includes an intelligent algorithm developed to intelligently detect whether a parameter has exceeded a threshold, which may or may not involve urgency. To verify the proper functioning of this system, we developed a small portable device capable of measuring the level of glucose in the blood for diabetics and body temperature. We designed a secure mechanism to establish a wireless connection with the smartphone.
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Maldonado, Kenly, and Steve Simske. "Situational Strategic Awareness Monitoring Surveillance System–Microcomputer and Microcomputer Clustering used for Intelligent, Economical, Scalable, and Deployable Approach for Safeguarding Materials." Electronic Imaging 2020, no. 3 (January 26, 2020): 60408–1. http://dx.doi.org/10.2352/issn.2470-1173.2020.3.mobmu-336.

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The principal objective of this research is to create a system that is quickly deployable, scalable, adaptable, and intelligent and provides cost-effective surveillance, both locally and globally. The intelligent surveillance system should be capable of rapid implementation to track (monitor) sensitive materials, i.e., radioactive or weapons stockpiles and person(s) within rooms, buildings, and/or areas in order to predict potential incidents proactively (versus reactively) through intelligence, locally and globally. The system will incorporate a combination of electronic systems that include commercial and modifiable off-the-shelf microcomputers to create a microcomputer cluster which acts as a mini supercomputer which leverages real-time data feed if a potential threat is present. Through programming, software, and intelligence (artificial intelligence, machine learning, and neural networks), the system should be capable of monitoring, tracking, and warning (communicating) the system observer operations (command and control) within a few minutes when sensitive materials are at potential risk for loss. The potential customer is government agencies looking to control sensitive materials and/or items in developing world markets intelligently, economically, and quickly.
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Maldonado, Kenly, and Steve Simske. "Situational Strategic Awareness Monitoring Surveillance System—Microcomputer and Microcomputer Clustering used for Intelligent, Economical, Scalable, and Deployable Approach for Safeguarding Materials." Journal of Imaging Science and Technology 63, no. 6 (November 1, 2019): 60408–1. http://dx.doi.org/10.2352/j.imagingsci.technol.2019.63.6.060408.

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Abstract The principal objective of this research is to create a system that is quickly deployable, scalable, adaptable, and intelligent and provides cost-effective surveillance, both locally and globally. The intelligent surveillance system should be capable of rapid implementation to track (monitor) sensitive materials, i.e., radioactive or weapons stockpiles and person(s) within rooms, buildings, and/or areas in order to predict potential incidents proactively (versus reactively) through intelligence, locally and globally. The system will incorporate a combination of electronic systems that include commercial and modifiable off-the-shelf microcomputers to create a microcomputer cluster which acts as a mini supercomputer which leverages real-time data feed if a potential threat is present. Through programming, software, and intelligence (artificial intelligence, machine learning, and neural networks), the system should be capable of monitoring, tracking, and warning (communicating) the system observer operations (command and control) within a few minutes when sensitive materials are at potential risk for loss. The potential customer is government agencies looking to control sensitive materials and/or items in developing world markets intelligently, economically, and quickly.
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Rothkrantz, Leon, Madalina Toma, and Mirela Popa. "AN INTELLIGENT CO-DRIVER SURVEILLANCE SYSTEM." Acta Polytechnica CTU Proceedings 12 (December 15, 2017): 83. http://dx.doi.org/10.14311/app.2017.12.0083.

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In recent years many car manufacturers developed digital co-drivers , which are able to monitor the driving behaviour of a car. Sensors in the car measure if a car passes speed limits, leaves its lane, or violates other traffic rules. A new generation of co-drivers is based on sensors in the car which are able to monitor the driver behaviour. Driving a car is a sequence of actions. In case a driver doesn’t show one of the actions the co-driver generates a warning signal. Experiments in the car simulator TORC were performed to extract the actions of a car driver. These actions were used to develop probabilistic models of the driving behaviour. A prototype of a warning system has been developed and tested in the car simulator. The experiments and test results will be reported in this paper.
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Sasikala, G., and R. S. Lekha. "Intelligent Surveillance System for Smart Security." Indian Journal of Science and Technology 12, no. 29 (August 1, 2019): 1–9. http://dx.doi.org/10.17485/ijst/2019/v12i29/147083.

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Nam, Yunyoung, Seungmin Rho, and Jong Hyuk Park. "Intelligent video surveillance system: 3-tier context-aware surveillance system with metadata." Multimedia Tools and Applications 57, no. 2 (December 22, 2010): 315–34. http://dx.doi.org/10.1007/s11042-010-0677-x.

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Mahibha, Akshaya S. Yamini E. Veeshal Sheev V. B. C. Jerin. "An Intelligent Fire Detection and Surveillance System." International Journal of Computer Sciences and Engineering 06, no. 03 (April 30, 2018): 158–62. http://dx.doi.org/10.26438/ijcse/v6si3.158162.

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Dissertations / Theses on the topic "Intelligent surveillance system"

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Zhou, Han, and 周晗. "Intelligent video surveillance in a calibrated multi-camera system." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2011. http://hub.hku.hk/bib/B45989217.

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Charvat, Robert C. "Surveillance for Intelligent Emergency Response Robotic Aircraft (SIERRA Project)." University of Cincinnati / OhioLINK, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1337888115.

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Du, Ruixiang. "An Intelligent Portable Aerial Surveillance System: Modeling and Image Stitching." Digital WPI, 2013. https://digitalcommons.wpi.edu/etd-theses/859.

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"Unmanned Aerial Vehicles (UAVs) have been widely used in modern warfare for surveillance, reconnaissance and even attack missions. They can provide valuable battlefield information and accomplish dangerous tasks with minimal risk of loss of lives and personal injuries. However, existing UAV systems are far from perfect to meet all possible situations. One of the most notable situations is the support for individual troops. Besides the incapability to always provide images in desired resolution, currently available systems are either too expensive for large-scale deployment or too heavy and complex for a single solder. Intelligent Portable Aerial Surveillance System (IPASS), sponsored by the Air Force Research Laboratory (AFRL), is aimed at developing a low-cost, light-weight unmanned aerial vehicle that can provide sufficient battlefield intelligence for individual troops. The main contributions of this thesis are two-fold (1) the development and verification of a model-based flight simulation for the aircraft, (2) comparison of image stitching techniques to provide a comprehensive aerial surveillance information from multiple vision. To assist with the design and control of the aircraft, dynamical models are established at different complexity levels. Simulations with these models are implemented in Matlab to study the dynamical characteristics of the aircraft. Aerial images acquired from the three onboard cameras are processed after getting the flying platform built. How a particular image is formed from a camera and the general pipeline of the feature-based image stitching method are first introduced in the thesis. To better satisfy the needs of this application, a homography-based stitching method is studied. This method can greatly reduce computation time with very little compromise in the quality of the panorama, which makes real-time video display of the surroundings on the ground station possible. By implementing both of the methods for image stitching using OpenCV, a quantitative comparison in the performance is accomplished."
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Barake, Bassem. "Towards an intelligent surveillance system for public security at crowded places." Thesis, University of Ottawa (Canada), 2009. http://hdl.handle.net/10393/28258.

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Nowadays, safety and security of public areas has become the centre of attention, and especially after 9/11 attack. A visual surveillance for public security is proposed to meet the needs of public areas, such as shopping malls, train stations, airports, etc... Surveillance researchers from the computer vision have focused on building automated systems and have hardly adopted an approach, where human is involved in decision making with the help of computer inputs. Knowing that the fully automated systems have some advantages such as saving human power, and supporting remote monitoring, but in other hand, these systems are not often tended to work in complex environments. This thesis adopts a human-cum-machine centric approach, where this approach is followed in order to assist security personnel in the physical monitoring with the support of video surveillance. A proposed system is designed and developed, which provides security personnel with real-time information about any suspected person they want to suspect about. Using the security system's application, the officer has to identify the region within the surveilled area where the suspected person is located. Based on the region identified, the system delegates and controls nearest installed cameras to cover the region and then capture pictures of the scene. Once the suspected person is identified by the security personnel from the pictures captured, the corresponding information such as personal and contact information of the person is displayed and available to the security officers. The architecture of the system is based on web services technology, where many researches outlined the benefits of using web services in terms of scalability, reliability, and re-usability of its components. This thesis provides detailed information about the proposed system and its components, discusses the application's graphical user interface to be used by security personnel, and proposes a methodology to select and control installed security cameras to cover a region identified by security personnel.
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Valera, Espina Maria. "An approach for designing a real-time intelligent distributed surveillance system." Thesis, Kingston University, 2006. http://eprints.kingston.ac.uk/20298/.

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The main aim of this PhD is to investigate how a methodology rooted in systems engineering concepts can be established and applied to the design of distributed wide-area visual surveillance systems. Nowadays, the research community in surveillance systems tends to be mostly focused on the computer vision part of these systems, researching and developing more intelligent algorithms. The integration and finally the creation of the system per se, are usually regarded as a secondary priority. We postulate here that until a robust systems-centred, rather than algorithmic-centred approach is used, the realisation of realistic distributed surveillance systems is unlikely to happen. The future generation of surveillance systems can be categorised, from a system engineering point of view, as concurrent, distributed, embedded, real time systems. An important aspect of these systems is the inherent temporal diversity (heterogeneous timing) that arises from a variety of timing requirements and from the parallelisation and distribution of the processes that compose the system. Embedded, real-time systems are often naturally asynchronous. However, the computer vision part of these surveillance systems is commonly conceived and designed in a sequential and synchronous manner, in many cases using an object-oriented approach. Moreover, to cope with the distributed nature of these systems, technologies such as CORBA are applied. Designing processes in a synchronous manner plus the run-time overheads associated with object oriented implementations may cause communication bottlenecks. Perhaps more importantly, it may produce unpredictable behaviour of some components of the system and hence undetermined performance from a system as a whole. Clearly, this is a major problem on surveillance systems that can often be expected to be safety-critical. This research has explored the use of an alternative approach to object-orientation for the design and implementation of intelligent distributed surveillance systems. The approach is known as Real-Time Networks (exemplified by system engineering methodologies such as MASCOT and extensions such as DORIS). This approach is based conceptually on conceiving solutions as being naturally concurrent, from the highest level of abstraction, with concurrent activities communicating through well-defined data-centred mechanisms. The methodology favours a disciplined approach to design, which yields a modular structure that has close correspondence between functional elements in design and constructional elements for system integration. It is such characteristics that we believe will become essential in overcoming the complexities of going from small-scale computer vision prototypes to large-scale working systems. To justify the selection of this methodology, an overview of different software approach methods that may be used for designing wide-area intelligent surveillance systems is given. This is then, narrowed down to a comparison between Real-Time Networks and Object Orientation. The comparison is followed by an illustration of two different design solutions of an existing real-time distributed surveillance system called ADVISOR. One of the design solutions, based on Object Oriented concepts, uses CORBA as a means for the integration and distribution characteristics of the system. The other design solution, based on Real-Time Networks, uses DORIS methodology as a solution for the design of the system. Once the justification over the selection is done, a' novel design of a generic visual surveillance system using the proposed Real-Time Networks method is presented. Finally, the conclusions and future work are explained in the last chapter.
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Siddiqui, Abdul Jabbar. "A Robust Vehicle Make and Model Recognition System for ITS Applications." Thesis, Université d'Ottawa / University of Ottawa, 2015. http://hdl.handle.net/10393/33124.

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A real-time Vehicle Make and Model Recognition (VMMR) system is a significant component of security applications in Intelligent Transportation Systems (ITS). A highly accurate and real-time VMMR system significantly reduces the overhead cost of resources otherwise required. In this thesis, we present a VMMR system that provides very high classification rates and is robust to challenges like low illumination, occlusions, partial and non-frontal views. These challenges are encountered in realistic environments and high security areas like parking lots and public spaces (e.g., malls, stadiums, and airports). The VMMR problem is a multi-class classification problem with a peculiar set of issues and challenges like multiplicity, inter- and intra-make ambiguity among various vehicles makes and models, which need to be solved in an efficient and reliable manner to achieve a highly robust VMMR system. To reliably overcome the ambiguity challenges, a global features representation approach based on the Bag-of-Features paradigm is proposed. We extract key features from different make-model classes in an optimized dictionary, through two different dictionary building strategies. We represent different samples from each class with respect to the learned dictionary. We also present two classification schemes based on multi-class Support Vector Machines (SVMs): (1) Single multi-class SVM and (2) Attribute Bagging-based Ensemble of multi-class SVMs. These classification schemes allow simultaneous learning of the differences between global representations of different classes and the similarities between different shapes or generations within a same make-model class, to further overcome the multiplicity challenges for real-time application. Extensive experiments conducted using our approaches yield superior results for images that were occluded, under low illumination, partial camera views, or even non-frontal views, available in a recently published real-world VMMR dataset. The approaches presented herewith provide a highly accurate VMMR system for real-time applications in realistic environments.
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Liu, Junbin. "Distributed low-power image processing in wireless sensor networks for intelligent video surveillance applications." Thesis, Queensland University of Technology, 2012. https://eprints.qut.edu.au/63311/1/Junbin_Liu_Thesis.pdf.

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Distributed Wireless Smart Camera (DWSC) network is a special type of Wireless Sensor Network (WSN) that processes captured images in a distributed manner. While image processing on DWSCs sees a great potential for growth, with its applications possessing a vast practical application domain such as security surveillance and health care, it suffers from tremendous constraints. In addition to the limitations of conventional WSNs, image processing on DWSCs requires more computational power, bandwidth and energy that presents significant challenges for large scale deployments. This dissertation has developed a number of algorithms that are highly scalable, portable, energy efficient and performance efficient, with considerations of practical constraints imposed by the hardware and the nature of WSN. More specifically, these algorithms tackle the problems of multi-object tracking and localisation in distributed wireless smart camera net- works and optimal camera configuration determination. Addressing the first problem of multi-object tracking and localisation requires solving a large array of sub-problems. The sub-problems that are discussed in this dissertation are calibration of internal parameters, multi-camera calibration for localisation and object handover for tracking. These topics have been covered extensively in computer vision literatures, however new algorithms must be invented to accommodate the various constraints introduced and required by the DWSC platform. A technique has been developed for the automatic calibration of low-cost cameras which are assumed to be restricted in their freedom of movement to either pan or tilt movements. Camera internal parameters, including focal length, principal point, lens distortion parameter and the angle and axis of rotation, can be recovered from a minimum set of two images of the camera, provided that the axis of rotation between the two images goes through the camera's optical centre and is parallel to either the vertical (panning) or horizontal (tilting) axis of the image. For object localisation, a novel approach has been developed for the calibration of a network of non-overlapping DWSCs in terms of their ground plane homographies, which can then be used for localising objects. In the proposed approach, a robot travels through the camera network while updating its position in a global coordinate frame, which it broadcasts to the cameras. The cameras use this, along with the image plane location of the robot, to compute a mapping from their image planes to the global coordinate frame. This is combined with an occupancy map generated by the robot during the mapping process to localised objects moving within the network. In addition, to deal with the problem of object handover between DWSCs of non-overlapping fields of view, a highly-scalable, distributed protocol has been designed. Cameras that follow the proposed protocol transmit object descriptions to a selected set of neighbours that are determined using a predictive forwarding strategy. The received descriptions are then matched at the subsequent camera on the object's path using a probability maximisation process with locally generated descriptions. The second problem of camera placement emerges naturally when these pervasive devices are put into real use. The locations, orientations, lens types etc. of the cameras must be chosen in a way that the utility of the network is maximised (e.g. maximum coverage) while user requirements are met. To deal with this, a statistical formulation of the problem of determining optimal camera configurations has been introduced and a Trans-Dimensional Simulated Annealing (TDSA) algorithm has been proposed to effectively solve the problem.
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Lorio, Berino. "Towards a non-intrusive traffic surveillance system using digital image processing." Thesis, Stellenbosch : Stellenbosch University, 2001. http://hdl.handle.net/10019.1/52589.

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Thesis (MScEng)--Stellenbosch University, 2001.
ENGLISH ABSTRACT: With the increased focus on the use of innovative and state-of-the-art technology in Intelligent Transport Systems (ITS), the need for more accurate and more detailed road traffic flow data has become apparent. Data obtained from vehicle detector loops, which merely act as vehicle presence sensors, is neither reliable nor accurate enough anymore. This type of sensor poses the problem that it has to be inserted into the road surface; temporarily obstructing traffic flows, and has to be replaced after pavement reconstruction. One of the solutions to this problem is to develop a traffic surveillance system that uses video image processing. In cities where Intelligent Transport Systems are used extensively, roadways are monitored through Closed Circuit Television Cameras (CCTV) that are closely watched by traffic control centre personnel. These cameras are mounted on posts on the roadside. These cameras can serve a dual purpose, being used for both human monitoring and as inputs to Video Image Processing Systems. In this study some of the digital image processing techniques that could be used in a traffic surveillance system were investigated. This report leads the reader through the various steps in the processing of a scene by a traffic surveillance system based on feature tracking, and discusses the pitfalls and problems that are experienced. The tracker was tested using three image sequences and the results are presented in the final chapter of this report.
AFRIKAANSE OPSOMMING: Met die toenemende fokus op die gebruik van innoverende oplossings en gevorderde tegnologie in Intelligente Vervoerstelsels, het die noodsaaklikheid van akkurater en meer gedetailleerde padverkeer vloeidata duidelik geword. Data wat verkry word d.m.v. voertuig deteksie lusse, wat alleenlik voertuig teenwoordigheid/afwesigheid meet, is nie meer akkuraat of betroubaar genoeg nie. Hierdie tipe sensors het egter die nadeel dat dit in die plaveisel ingesny moet word, dus vloei tydelik kan belemmer, en moet vervang word elke keer as plaveisel rekonstruksie gedoen word. Een van die oplossings vir hierdie probleem is om 'n verkeers waarnemingstelsel te ontwikkel wat van videobeeldverwerking gebruik maak. In stede waar van uitgebreide intelligente verkeerstelsels gebruik gemaak word, word paaie gemonitor d.m.v. geslote baan televisiekameras wat op pale langs die paaie aangebring is. Personeellede van die verkeers beheer sentrum hou dan die inkomende televisiebeelde dop. Hierdie kameras kan 'n dubelle rol vervul deurdat dit vir beide menslike waarneming en as invoer in 'n video-beeldverwerking stelsel gebruik kan word. In hierdie studie was verskeie digitale beeldverwerking tegnieke wat gebruik kan word in 'n verkeers waarnemingstelsel ondersoek. Hierdie verslag lei die leser deur die verskeie stappe in die verwerking van 'n toneel deur 'n verkeers waarneming stelsel wat gebaseer is op die volg van kenmerke. Die verslag beskryf ook die slaggate en probleme wat ondervind word. Die voertuig volger was getoets deur van drie reekse beelde gebruik te maak en die resultate word weergegee in die finale hoodfstuk van hierdie verslag.
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Sugianto, Nehemia. "Responsible AI for Automated Analysis of Integrated Video Surveillance in Public Spaces." Thesis, Griffith University, 2021. http://hdl.handle.net/10072/409586.

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Understanding customer experience in real-time can potentially support people’s safety and comfort while in public spaces. Existing techniques, such as surveys and interviews, can only analyse data at specific times. Therefore, organisations that manage public spaces, such as local government or business entities, cannot respond immediately when urgent actions are needed. Manual monitoring through surveillance cameras can enable organisation personnel to observe people. However, fatigue and human distraction during constant observation cannot ensure reliable and timely analysis. Artificial intelligence (AI) can automate people observation and analyse their movement and any related properties in real-time. Analysing people’s facial expressions can provide insight into how comfortable they are in a certain area, while analysing crowd density can inform us of the area’s safety level. By observing the long-term patterns of crowd density, movement, and spatial data, the organisation can also gain insight to develop better strategies for improving people’s safety and comfort. There are three challenges to making an AI-enabled video surveillance system work well in public spaces. First is the readiness of AI models to be deployed in public space settings. Existing AI models are designed to work in generic/particular settings and will suffer performance degradation when deployed in a real-world setting. Therefore, the models require further development to tailor them for the specific environment of the targeted deployment setting. Second is the inclusion of AI continual learning capability to adapt the models to the environment. AI continual learning aims to learn from new data collected from cameras to adapt the models to constant visual changes introduced in the setting. Existing continuous learning approaches require long-term data retention and past data, which then raise data privacy issues. Third, most of the existing AI-enabled surveillance systems rely on centralised processing, meaning data are transmitted to a central/cloud machine for video analysis purposes. Such an approach involves data privacy and security risks. Serious data threats, such as data theft, eavesdropping or cyberattack, can potentially occur during data transmission. This study aims to develop an AI-enabled intelligent video surveillance system based on deep learning techniques for public spaces established on responsible AI principles. This study formulates three responsible AI criteria, which become the guidelines to design, develop, and evaluate the system. Based on the criteria, a framework is constructed to scale up the system over time to be readily deployed in a specific real-world environment while respecting people’s privacy. The framework incorporates three AI learning approaches to iteratively refine the AI models within the ethical use of data. First is the AI knowledge transfer approach to adapt existing AI models from generic deployment to specific real-world deployment with limited surveillance datasets. Second is the AI continuous learning approach to continuously adapt AI models to visual changes introduced by the environment without long-period data retention and the need for past data. Third is the AI federated learning approach to limit sensitive and identifiable data transmission by performing computation locally on edge devices rather than transmitting to the central machine. This thesis contributes to the study of responsible AI specifically in the video surveillance context from both technical and non-technical perspectives. It uses three use cases at an international airport as the application context to understand passenger experience in real-time to ensure people’s safety and comfort. A new video surveillance system is developed based on the framework to provide automated people observation in the application context. Based on real deployment using the airport’s selected cameras, the evaluation demonstrates that the system can provide real-time automated video analysis for three use cases while respecting people’s privacy. Based on comprehensive experiments, AI knowledge transfer can be an effective way to address limited surveillance datasets issue by transferring knowledge from similar datasets rather than training from scratch on surveillance datasets. It can be further improved by incrementally transferring knowledge from multi-datasets with smaller gaps rather than a one-stage process. Learning without Forgetting is a viable approach for AI continuous learning in the video surveillance context. It consistently outperforms fine-tuning and joint-training approaches with lower data retention and without the need for past data. AI federated learning can be a feasible solution to allow continuous learning in the video surveillance context without compromising model accuracy. It can obtain comparable accuracy with quicker training time compared to joint-training.
Thesis (PhD Doctorate)
Doctor of Philosophy (PhD)
Dept Bus Strategy & Innovation
Griffith Business School
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Chen, Jiandan. "An Intelligent Multi Sensor System for a Human Activities Space---Aspects of Quality Measurement and Sensor Arrangement." Doctoral thesis, Karlskrona : Blekinge Institute of Technology, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-00487.

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In our society with its aging population, the design and implementation of a highperformance distributed multi-sensor and information system for autonomous physical services become more and more important. In line with this, this thesis proposes an Intelligent Multi-Sensor System, IMSS, that surveys a human activities space to detect and identify a target for a specific service. The subject of this thesis covers three main aspects related to the set-up of an IMSS: an improved depth measurement and reconstruction method and its related uncertainty, a surveillance and tracking algorithm and finally a way to validate and evaluate the proposed methods and algorithms. The thesis discusses how a model of the depth spatial quantisation uncertainty can be implemented to optimize the configuration of a sensor system to capture information of the target objects and their environment with required specifications. The thesis introduces the dithering algorithm which significantly reduces the depth reconstruction uncertainty. Furthermore, the dithering algorithm is implemented on a sensor-shifted stereo camera, thus simplifying depth reconstruction without compromising the common stereo field of view. To track multiple targets continuously, the Gaussian Mixture Probability Hypothesis Density, GM-PHD, algorithm is implemented with the help of vision and Radio Frequency Identification, RFID, technologies. The performance of the tracking algorithm in a vision system is evaluated by a circular motion test signal. The thesis introduces constraints to the target space, the stereo pair characteristics and the depth reconstruction accuracy to optimize the vision system and to control the performance of surveillance and 3D reconstruction through integer linear programming. The human being within the activity space is modelled as a tetrahedron, and a field of view in spherical coordinates are used in the control algorithms. In order to integrate human behaviour and perception into a technical system, the proposed adaptive measurement method makes use of the Fuzzily Defined Variable, FDV. The FDV approach enables an estimation of the quality index based on qualitative and quantitative factors for image quality evaluation using a neural network. The thesis consists of two parts, where Part I gives an overview of the applied theory and research methods used, and Part II comprises the eight papers included in the thesis.
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Books on the topic "Intelligent surveillance system"

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Qian, Huihuan, Xinyu Wu, and Yangsheng Xu. Intelligent Surveillance Systems. Dordrecht: Springer Netherlands, 2011. http://dx.doi.org/10.1007/978-94-007-1137-2.

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Xinyu, Wu, Xu Yangsheng, and SpringerLink (Online service), eds. Intelligent Surveillance Systems. Dordrecht: Springer Science+Business Media B.V., 2011.

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Dufour, Jean-Yves, ed. Intelligent Video Surveillance Systems. Hoboken, NJ USA: John Wiley & Sons, Inc., 2012. http://dx.doi.org/10.1002/9781118577851.

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Dufour, Jean-Yves. Intelligent video surveillance systems. London: ISTE, 2013.

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A, Velastin Sergio, Remagnino Paolo 1963-, and Institution of Electrical Engineers, eds. Intelligent distributed video surveillance systems. London: Institution of Electrical Engineers, 2006.

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Intelligent video surveillance: Systems and technology. Boca Raton: CRC Press, 2010.

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Yunqian, Ma, and Qian G. 1973-, eds. Intelligent video surveillance: Systems and technology. Boca Raton: CRC Press, 2010.

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Nilsson, Fredrik. Intelligent network video: Understanding modern video surveillance systems. Boca Raton: Taylor & Francis, 2008.

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Nilsson, Fredrik. Intelligent network video: Understanding modern video surveillance systems. Boca Raton: Taylor & Francis, 2008.

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Johnson, William M. Eavesdropping, technical surveillance & technical surveillance countermeasures. Seattle, WA: Business Espionage Controls & Countermeasures Association, 1993.

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Book chapters on the topic "Intelligent surveillance system"

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Kukan, S., S. Gokul, S. S. Vishnu Priyan, S. Barathi Kanna, and E. Prabhu. "COVID-19: Smart Shop Surveillance System." In Intelligent Sustainable Systems, 711–23. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-2422-3_55.

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Kiran, S. L., and M. Supriya. "Cost Efficient Intelligent Vehicle Surveillance System." In Information and Communication Technology for Intelligent Systems (ICTIS 2017) - Volume 1, 270–77. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-63673-3_32.

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Jaiswal, Anshuman, Lavkush Sharma, Akshay Kumar, and Suryansh Chauhan. "Intelligent Surveillance System Using Machine Learning." In Industry 4.0, AI, and Data Science, 123–33. New York: CRC Press, 2021. http://dx.doi.org/10.1201/9781003097181-8.

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Deshmukh, Abhishek, Kshitij Warang, Yash Pente, and Nilesh Marathe. "Violence Detection Through Surveillance System." In Advances in Intelligent Systems and Computing, 503–11. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-8289-9_49.

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Venkatesan, R., P. Dinesh Anton Raja, and A. Balaji Ganesh. "Video Surveillance Based Tracking System." In Advances in Intelligent Systems and Computing, 369–78. New Delhi: Springer India, 2014. http://dx.doi.org/10.1007/978-81-322-2126-5_41.

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Murphey, Yi L., Henry Lu, Robert Karlsen, Grant Gerhart, and Thomas Meitzler. "Dyta: An Intelligent System for Dynamic Target Analysis." In Multimedia Video-Based Surveillance Systems, 118–29. Boston, MA: Springer US, 2000. http://dx.doi.org/10.1007/978-1-4615-4327-5_11.

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Rajesh, T. M., and Kavyashree Dalawai. "Automated Video Surveillance System Using Video Analytics." In Intelligent Computing and Communication, 451–61. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-1084-7_43.

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Eom, Ki-Yeol, Tae-Ki Ahn, Gyu-Jin Kim, Gyu-Jin Jang, and Moon-hyun Kim. "Fast Object Tracking in Intelligent Surveillance System." In Computational Science and Its Applications – ICCSA 2009, 749–63. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-02457-3_62.

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Bistry, Hannes, and Jianwei Zhang. "Development of an Intelligent Omnivision Surveillance System." In Advances in Intelligent Systems and Computing, 783–94. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-37835-5_68.

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Merta, Tomasz, and Andrzej Czyżewski. "Superresolution Algorithm to Video Surveillance System." In Advances in Intelligent and Soft Computing, 105–12. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-14989-4_10.

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Conference papers on the topic "Intelligent surveillance system"

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Banu, Virgil Claudiu, Ilona Madalina Costea, Florin Codrut Nemtanu, and Iulian Badescu. "Intelligent video surveillance system." In 2017 IEEE 23rd International Symposium for Design and Technology in Electronic Packaging (SIITME). IEEE, 2017. http://dx.doi.org/10.1109/siitme.2017.8259891.

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Kim, Byung Joo. "Developing Intelligent Surveillance System." In Circuits, Control, Communication, Electricity, Electronics, Energy, System, Signal and Simulation 2014. Science & Engineering Research Support soCiety, 2014. http://dx.doi.org/10.14257/astl.2014.51.07.

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Kumar, P. N. Pavan, M. Jain, A. Pavan, M. P. Bhat, and C. Manjunath. "Intelligent Collaborative Surveillance System." In 2013 International Conference on Advances in Technology and Engineering (ICATE 2013). IEEE, 2013. http://dx.doi.org/10.1109/icadte.2013.6524717.

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Gao, Siyuan. "An Intelligent Video Surveillance System." In 2010 International Conference on E-Product E-Service and E-Entertainment (ICEEE 2010). IEEE, 2010. http://dx.doi.org/10.1109/iceee.2010.5661050.

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Jiang, Yu, and Ke-Bin Jia. "IPv6 Based Intelligent Surveillance System." In 2011 International Conference on Multimedia and Signal Processing (CMSP). IEEE, 2011. http://dx.doi.org/10.1109/cmsp.2011.119.

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"Vision-based intelligent surveillance system." In 2017 10th International Conference on Human System Interactions (HSI). IEEE, 2017. http://dx.doi.org/10.1109/hsi.2017.8004994.

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Hargude, Sonali, and S. R. Idate. "i-surveillance: Intelligent surveillance system using background subtraction technique." In 2016 International Conference on Computing Communication Control and automation (ICCUBEA). IEEE, 2016. http://dx.doi.org/10.1109/iccubea.2016.7860046.

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Dsouza, Arnold, Aryan Fernandes, Alwin Jacob, and Amroz Siddiqui. "Artificial Intelligence Surveillance System." In 2022 International Conference on Computing, Communication, Security and Intelligent Systems (IC3SIS). IEEE, 2022. http://dx.doi.org/10.1109/ic3sis54991.2022.9885659.

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Altunay, Damla Gul, Naciye Karademir, Okan Topcu, and Cem Direkoglu. "Intelligent surveillance system for abandoned luggage." In 2018 26th Signal Processing and Communications Applications Conference (SIU). IEEE, 2018. http://dx.doi.org/10.1109/siu.2018.8404327.

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Zhang, Weidong, Feng Chen, Wenli Xu, and Enwei Zhang. "Real-Time Video Intelligent Surveillance System." In 2006 IEEE International Conference on Multimedia and Expo. IEEE, 2006. http://dx.doi.org/10.1109/icme.2006.262707.

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Reports on the topic "Intelligent surveillance system"

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Rhody, Harvey, David Sher, and James Modestino. Intelligent Signal Processing Techniques for Multi-Sensor Surveillance Systems. Fort Belvoir, VA: Defense Technical Information Center, December 1989. http://dx.doi.org/10.21236/ada218890.

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Shi, Leyuan. An Optimization Framework for Intelligence, Surveillance, and Reconnaissance Systems. Fort Belvoir, VA: Defense Technical Information Center, April 2007. http://dx.doi.org/10.21236/ada473334.

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Acharya, Ashwin, Max Langenkamp, and James Dunham. Trends in AI Research for the Visual Surveillance of Populations. Center for Security and Emerging Technology, January 2022. http://dx.doi.org/10.51593/20200097.

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Progress in artificial intelligence has led to growing concern about the capabilities of AI-powered surveillance systems. This data brief uses bibliometric analysis to chart recent trends in visual surveillance research — what share of overall computer vision research it comprises, which countries are leading the way, and how things have varied over time.
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McRae, Stuart J. Overhauling the Airborne Intelligence, Surveillance, and Reconnaissance Systems Procurement Process. Fort Belvoir, VA: Defense Technical Information Center, March 2011. http://dx.doi.org/10.21236/ada543175.

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Murray, Chris, Keith Williams, Norrie Millar, Monty Nero, Amy O'Brien, and Damon Herd. A New Palingenesis. University of Dundee, November 2022. http://dx.doi.org/10.20933/100001273.

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Robert Duncan Milne (1844-99), from Cupar, Fife, was a pioneering author of science fiction stories, most of which appeared in San Francisco’s Argonaut magazine in the 1880s and ’90s. SF historian Sam Moskowitz credits Milne with being the first full-time SF writer, and his contribution to the genre is arguably greater than anyone else including Stevenson and Conan Doyle, yet it has all but disappeared into oblivion. Milne was fascinated by science. He drew on the work of Scottish physicists and inventors such as James Clark Maxwell and Alexander Graham Bell into the possibilities of electromagnetic forces and new communications media to overcome distances in space and time. Milne wrote about visual time-travelling long before H.G. Wells. He foresaw virtual ‘tele-presencing’, remote surveillance, mobile phones and worldwide satellite communications – not to mention climate change, scientific terrorism and drone warfare, cryogenics and molecular reengineering. Milne also wrote on alien life forms, artificial immortality, identity theft and personality exchange, lost worlds and the rediscovery of extinct species. ‘A New Palingenesis’, originally published in The Argonaut on July 7th 1883, and adapted in this comic, is a secular version of the resurrection myth. Mary Shelley was the first scientiser of the occult to rework the supernatural idea of reanimating the dead through the mysterious powers of electricity in Frankenstein (1818). In Milne’s story, in which Doctor S- dissolves his terminally ill wife’s body in order to bring her back to life in restored health, is a striking, further modernisation of Frankenstein, to reflect late-nineteenth century interest in electromagnetic science and spiritualism. In particular, it is a retelling of Shelley’s narrative strand about Frankenstein’s aborted attempt to shape a female mate for his creature, but also his misogynistic ambition to bypass the sexual principle in reproducing life altogether. By doing so, Milne interfused Shelley’s updating of the Promethean myth with others. ‘A New Palingenesis’ is also a version of Pygmalion and his male-ordered, wish-fulfilling desire to animate his idealised female sculpture, Galatea from Ovid’s Metamorphoses, perhaps giving a positive twist to Orpheus’s attempt to bring his corpse-bride Eurydice back from the underworld as well? With its basis in spiritualist ideas about the soul as a kind of electrical intelligence, detachable from the body but a material entity nonetheless, Doctor S- treats his wife as an ‘intelligent battery’. He is thus able to preserve her personality after death and renew her body simultaneously because that captured electrical intelligence also carries a DNA-like code for rebuilding the individual organism itself from its chemical constituents. The descriptions of the experiment and the body’s gradual re-materialisation are among Milne’s most visually impressive, anticipating the X-raylike anatomisation and reversal of Griffin’s disappearance process in Wells’s The Invisible Man (1897). In the context of the 1880s, it must have been a compelling scientisation of the paranormal, combining highly technical descriptions of the Doctor’s system of electrically linked glass coffins with ghostly imagery. It is both dramatic and highly visual, even cinematic in its descriptions, and is here brought to life in the form of a comic.
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