Relevant bibliographies by topics / Distributed algorithms for camera networks

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
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Academic literature on the topic 'Distributed algorithms for camera networks'

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Published: 6 September 2023

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Journal articles on the topic "Distributed algorithms for camera networks"

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Anjum, Nadeem. "Camera Localization in Distributed Networks Using Trajectory Estimation." Journal of Electrical and Computer Engineering 2011 (2011): 1–13. http://dx.doi.org/10.1155/2011/604647.

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This paper presents an algorithm for camera localization using trajectory estimation (CLUTE) in a distributed network of nonoverlapping cameras. The algorithm recovers the extrinsic calibration parameters, namely, the relative position and orientation of the camera network on a common ground plane coordinate system. We first model the observed trajectories in each camera's field of view using Kalman filtering, then we use this information to estimate the missing trajectory information in the unobserved areas by fusing the results of a forward and backward linear regression estimation from adjacent cameras. These estimated trajectories are then filtered and used to recover the relative position and orientation of the cameras by analyzing the estimated and observedexitandentrypoints of an object in each camera's field of view. The final configuration of the network is established by considering one camera as a reference and by adjusting the remaining cameras with respect to this reference. We demonstrate the algorithm on both simulated and real data and compare the results with state-of-the-art approaches. The experimental results show that the proposed algorithm is more robust to noisy and missing data and in case of camera failure.
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Zhao, Long, Zhen Liu, Tiejun Li, Baoqi Huang, and Lihua Xie. "Moving Target Positioning Based on a Distributed Camera Network." Mathematical Problems in Engineering 2014 (2014): 1–11. http://dx.doi.org/10.1155/2014/803743.

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We propose a systematic framework for moving target positioning based on a distributed camera network. In the proposed framework, low-cost static cameras are deployed to cover a large region, moving targets are detected and then tracked using corresponding algorithms, target positions are estimated by making use of the geometrical relationships among those cameras after calibrating those cameras, and finally, for each target, its position estimates obtained from different cameras are unified into the world coordinate system. This system can function as complementary positioning information sources to realize moving target positioning in indoor or outdoor environments when global navigation satellite system (GNSS) signals are unavailable. The experiments are carried out using practical indoor and outdoor environment data, and the experimental results show that the systematic framework and inclusive algorithms are both effective and efficient.
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Wu, Yi-Chang, Ching-Han Chen, Yao-Te Chiu, and Pi-Wei Chen. "Cooperative People Tracking by Distributed Cameras Network." Electronics 10, no. 15 (July 25, 2021): 1780. http://dx.doi.org/10.3390/electronics10151780.

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In the application of video surveillance, reliable people detection and tracking are always challenging tasks. The conventional single-camera surveillance system may encounter difficulties such as narrow-angle of view and dead space. In this paper, we proposed multi-cameras network architecture with an inter-camera hand-off protocol for cooperative people tracking. We use the YOLO model to detect multiple people in the video scene and incorporate the particle swarm optimization algorithm to track the person movement. When a person leaves the area covered by a camera and enters an area covered by another camera, these cameras can exchange relevant information for uninterrupted tracking. The motion smoothness (MS) metrics is proposed for evaluating the tracking quality of multi-camera networking system. We used a three-camera system for two persons tracking in overlapping scene for experimental evaluation. Most tracking person offsets at different frames were lower than 30 pixels. Only 0.15% of the frames showed abrupt increases in offsets pixel. The experiment results reveal that our multi-camera system achieves robust, smooth tracking performance.
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Eriksson, Emil, Gyorgy Dan, and Viktoria Fodor. "Coordinating Distributed Algorithms for Feature Extraction Offloading in Multi-Camera Visual Sensor Networks." IEEE Transactions on Circuits and Systems for Video Technology 28, no. 11 (November 2018): 3288–99. http://dx.doi.org/10.1109/tcsvt.2017.2745102.

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Giordano, Jacopo, Margherita Lazzaretto, Giulia Michieletto, and Angelo Cenedese. "Visual Sensor Networks for Indoor Real-Time Surveillance and Tracking of Multiple Targets." Sensors 22, no. 7 (March 30, 2022): 2661. http://dx.doi.org/10.3390/s22072661.

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The recent trend toward the development of IoT architectures has entailed the transformation of the standard camera networks into smart multi-device systems capable of acquiring, elaborating, and exchanging data and, often, dynamically adapting to the environment. Along this line, this work proposes a novel distributed solution that guarantees the real-time monitoring of 3D indoor structured areas and also the tracking of multiple targets, by employing a heterogeneous visual sensor network composed of both fixed and Pan-Tilt-Zoom (PTZ) cameras. The fulfillment of the twofold mentioned goal was ensured through the implementation of a distributed game-theory-based algorithm, aiming at optimizing the controllable parameters of the PTZ devices. The proposed solution is able to deal with the possible conflicting requirements of high tracking precision and maximum coverage of the surveilled area. Extensive numerical simulations in realistic scenarios validated the effectiveness of the outlined strategy.
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Chebi, Hocine, Abdelkader Benaissa, and Rafik Sayah. "Contribution to the Maximum Coverage Detection in a Heterogeneous Network." International Journal of Applied Evolutionary Computation 11, no. 3 (July 2020): 1–19. http://dx.doi.org/10.4018/ijaec.2020070101.

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This article has addressed the problem of area coverage in surveillance camera networks using a minimum number of active sensors. The dense and random deployment of cameras creates many problems, among which the same portion of the area of interest is cited and monitored by several sensors. This redundancy of information generates unnecessary energy consumption, which increases the cost of installation. This work contributed to the extension of a surveillance algorithm, and the authors presented in this work a distributed algorithm of perimeter surveillance and made this contribution allowing the maintenance of total coverage in heterogeneous camera networks. The proposed solution is based on the search for minimum sets that completely cover a surface by scheduling the activity of the sensors. The proposed approach consists of calculating the distance between the center and the furthest point not covered and subtracting a fixed step from it; the coverage of these circles is done in the same way as the coverage of the first perimeter. The results of the simulations show that this approach ensures maximum coverage with a minimum number of cameras.
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Song, Wenzhan, Fangyu Li, Maria Valero, and Liang Zhao. "Toward Creating a Subsurface Camera." Sensors 19, no. 2 (January 14, 2019): 301. http://dx.doi.org/10.3390/s19020301.

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In this article, the framework and architecture of a Subsurface Camera (SAMERA) are envisioned and described for the first time. A SAMERA is a geophysical sensor network that senses and processes geophysical sensor signals and computes a 3D subsurface image in situ in real time. The basic mechanism is geophysical waves propagating/reflected/refracted through subsurface enter a network of geophysical sensors, where a 2D or 3D image is computed and recorded; control software may be connected to this network to allow view of the 2D/3D image and adjustment of settings such as resolution, filter, regularization, and other algorithm parameters. System prototypes based on seismic imaging have been designed. SAMERA technology is envisioned as a game changer to transform many subsurface survey and monitoring applications, including oil/gas exploration and production, subsurface infrastructures and homeland security, wastewater and CO2 sequestration, and earthquake and volcano hazard monitoring. System prototypes for seismic imaging have been built. Creating SAMERA requires interdisciplinary collaboration and the transformation of sensor networks, signal processing, distributed computing, and geophysical imaging.
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Chen, Yanming, Qingjie Zhao, Zhulin An, Peng Lv, and Liujun Zhao. "Distributed Multi-Target Tracking Based on the K-MTSCF Algorithm in Camera Networks." IEEE Sensors Journal 16, no. 13 (July 2016): 5481–90. http://dx.doi.org/10.1109/jsen.2016.2565263.

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Luo, Jiajia, Wei Wang, and Hairong Qi. "Feature Extraction and Representation for Distributed Multi-View Human Action Recognition." Emerging and Selected Topics in Circuits and Systems, IEEE Journal on 3, no. 2 (June 2013): 145–54. http://dx.doi.org/10.1109/jetcas.2013.2256824.

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Multi-view human action recognition has gained a lot of attention in recent years for its superior performance as compared to single view recognition. In this paper, we propose a new framework for the real-time realization of human action recognition in distributed camera networks (DCNs). We first present a new feature descriptor (Mltp-hist) that is tolerant to illumination change, robust in homogeneous region and computationally efficient. Taking advantage of the proposed Mltp-hist, the noninformative 3-D patches generated from the background can be further removed automatically that effectively highlights the foreground patches. Next, a new feature representation method based on sparse coding is presented to generate the histogram representation of local videos to be transmitted to the base station for classification. Due to the sparse representation of extracted features, the approximation error is reduced. Finally, at the base station, a probability model is produced to fuse the information from various views and a class label is assigned accordingly. Compared to the existing algorithms, the proposed framework has three advantages while having less requirements on memory and bandwidth consumption: 1) no preprocessing is required; 2) communication among cameras is unnecessary; and 3) positions and orientations of cameras do not need to be fixed. We further evaluate the proposed framework on the most popular multi-view action dataset IXMAS. Experimental results indicate that our proposed framework repeatedly achieves state-of-the-art results when various numbers of views are tested. In addition, our approach is tolerant to the various combination of views and benefit from introducing more views at the testing stage. Especially, our results are still satisfactory even when large misalignment exists between the training and testing samples.
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Niu, Zhenyu. "Voice Detection and Deep Learning Algorithms Application in Remote English Translation Classroom Monitoring." Mobile Information Systems 2022 (July 21, 2022): 1–10. http://dx.doi.org/10.1155/2022/3340999.

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With the continuous development of cellular networks, the traffic from voice services increases gradually. The wireless sensor network (WSN) is a distributed network consisting of a large number of peripheral nodes distributed in the surveillance area. The nodes in the network complete it in a self-organizing form, and the sink node collects the data from each sensor node. When sending data, the nodes near the receiver will quickly run out of energy and cannot perform further transmission tasks. The resulting “power supply emptiness” problem has a great impact on network performance. Therefore, the power consumption of the network must be considered when designing the WSN routing algorithm. In order to effectively improve students’ academic performance and monitor students’ teaching conditions, the classroom remote monitoring system places two cameras in the university’s English translation classroom and uses technology to merge the information to execute the entire process. By recording the course, we can save the teacher’s classroom content and the student’s classroom performance and upload the recorded video in real time. In addition, the classroom remote monitoring system is a multiclient system, divided into teacher and student terminals. The user can log in, watch the video, and perform other necessary operations.
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Dissertations / Theses on the topic "Distributed algorithms for camera networks"

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Katragadda, Sandeep. "Distributed target tracking in wireless camera networks." Thesis, Queen Mary, University of London, 2017. http://qmro.qmul.ac.uk/xmlui/handle/123456789/25899.

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Distributed target tracking (DTT) is desirable in wireless camera networks to achieve scalability and robustness to node or link failures. DTT estimates the target state via information exchange and fusion among cameras. This thesis proposes new DTT algorithms to handle five major challenges of DTT in wireless camera networks, namely non-linearity in the camera measurement model, temporary lack of measurements (benightedness) due to limited field of view, redundant information in the network, limited connectivity of the network due to limited communication ranges and asynchronous information caused by varying and unknown frame processing delays. The algorithms consist of two phases, namely estimation and fusion. In the estimation phase, the cameras process their captured frames, detect the target, and estimate the target state (location and velocity) and its uncertainty using the Extended Information Filter (EIF) that handles non-linearity. In the fusion phase, the cameras exchange their local target information with their communicative neighbours and fuse the information. The contributions of this thesis are as follows. The target states estimated by the EIFs undergo weighted fusion. The weights are chosen based on the estimated uncertainty (error covariance) and the number of nodes with redundant information such that the information of benighted nodes and the redundant information get lower weights. At each time step, only the cameras having the view of the target and the cameras that might have the view of the target in the next time step participate in the fusion (tracking). This reduces the energy consumption of the network. The algorithm selects the cameras dynamically by using a threshold on their shortest distances (in the communication graph) from the cameras having the view of the target. Before fusion, each camera predicts the target information of other cameras to temporally align its information with the (asynchronous) information received from other cameras. The algorithm predicts the target state using the latest estimated velocity of the target. The experimental results show that the proposed algorithms achieve higher tracking accuracy than the state of the art under the five DTT challenges.
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Ramakrishnan, Naveen. "Distributed Learning Algorithms for Sensor Networks." The Ohio State University, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=osu1284991632.

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Hong, Kirak. "A distributed framework for situation awareness on camera networks." Diss., Georgia Institute of Technology, 2014. http://hdl.handle.net/1853/52263.

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With the proliferation of cameras and advanced video analytics, situation awareness applications that automatically generate actionable knowledge from live camera streams has become an important class of applications in various domains including surveillance, marketing, sports, health care, and traffic monitoring. However, despite the wide range of use cases, developing those applications on large-scale camera networks is extremely challenging because it involves both compute- and data-intensive workloads, has latency-sensitive quality of service requirement, and deals with inherent dynamism (e.g., number of faces detected in a certain area) from the real world. To support developing large-scale situation awareness applications, this dissertation presents a distributed framework that makes two key contributions: 1) it provides a programming model that ensures scalability of applications and 2) it supports low-latency computation and dynamic workload handling through opportunistic event processing and workload distribution over different locations and network hierarchy. To provide a scalable programming model, two programming abstractions for different levels of application logic are proposed: the first abstraction at the level of real-time target detection and tracking, and the second abstraction for answering spatio-temporal queries at a higher level. The first programming abstraction, Target Container (TC), elevates target as a first-class citizen, allowing domain experts to simply provide handlers for detection, tracking, and comparison of targets. With those handlers, TC runtime system performs priority-aware scheduling to ensure real-time tracking of important targets when resources are not enough to track all targets. The second abstraction, Spatio-temporal Analysis (STA) supports applications to answer queries related to space, time, and occupants using a global state transition table and probabilistic events. To ensure scalability, STA supports bounded communication overhead of state update by providing tuning parameters for the information propagation among distributed workers. The second part of this work explores two optimization strategies that reduce latency for stream processing and handle dynamic workload. The first strategy, an opportunistic event processing mechanism, performs event processing on predicted locations to provide just-in-time situational information to mobile users. Since location prediction algorithms are inherently inaccurate, the system selects multiple regions using a greedy algorithm to provide highly meaningful information at the given amount of computing resources. The second strategy is to distribute application workload over computing resources that are placed at different locations and various levels of network hierarchy. To support this strategy, the framework provides hierarchical communication primitives and a decentralized resource discovery protocol that allow scalable and highly adaptive load balancing over space and time.
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Song, Bi. "Scene analysis, control and communication in distributed camera networks." Diss., [Riverside, Calif.] : University of California, Riverside, 2009. http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:3359910.

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Thesis (Ph. D.)--University of California, Riverside, 2009.
Includes abstract. Title from first page of PDF file (viewed January 27, 2010). Includes bibliographical references (p. 99-105). Issued in print and online. Available via ProQuest Digital Dissertations.
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Mehrotra, Shashank. "Distributed Algorithms for Tasking Large Sensor Networks." Thesis, Virginia Tech, 2001. http://hdl.handle.net/10919/33975.

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Recent advances in wireless communications along with developments in low-power circuit design and micro-electro mechanical systems (MEMS) have heralded the advent of compact and inexpensive wireless micro-sensor devices. A large network of such sensor nodes capable of communicating with each other provides significant new capabilities for automatically collecting and analyzing data from physical environments. A notable feature of these networks is that more nodes than are strictly necessary may be deployed to cover a given region. This permits the system to provide reliable information, tolerate many types of faults, and prolong the effective service time. Like most wireless systems, achieving low power consumption is a key consideration in the design of these networks. This thesis presents algorithms for managing power at the distributed system level, rather than just at the individual node level. These distributed algorithms allocate work based on user requests to the individual sensor nodes that comprise the network. The primary goal of the algorithms is to provide a robust and scalable approach for tasking nodes that prolongs the effective life of the network. Theoretical analysis and simulation results are presented to characterize the behavior of these algorithms. Results obtained from simulation experiments indicate that the algorithms can achieve a significant increase in the life of the network. In some cases this may be by an order of magnitude. The algorithms are also shown to ensure a good quality of sensor coverage while improving the network life. Finally, they are shown to be robust to faults and scale to large numbers of nodes.
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Tomozei, Dan-Cristian. "Distributed algorithms for peer-to-peer networks." Paris 6, 2011. http://www.theses.fr/2011PA066059.

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La thèse comporte trois parties. Chaque partie est consacrée à un problème algorithmique important pour les réseaux pair-à-pair. Dans la première partie on analyse des méthodes distribuées cherchant à caractériser les préférences d'usagers: On étend l'applicabilité des méthodes spectrales pour la récupération de structures cachées à des modèles probabilistes de faible rang pour les goûts des usagers. Par la suite, on propose une méthode distribuée basée sur des échanges de messages (message passing) à deux échelles séparées de temps, qui effectue le profilage des usagers d'un réseau pair-à-pair. On montre que cette méthode converge presque sûrement vers les vecteurs propres d'une matrice de similitude des usagers. Dans la deuxième partie on considère le problème d'estimation de distances dans Internet et de sélection de serveur à base d'un faible nombre de mesures. On attribue à chaque noeud des coordonnées virtuelles dans un certain espace de faible dimension et on utilise une fonction de pseudo-distance dans cet espace afin d'estimer des latences et des débits. Supposant que les mesures sont des distorsions de quantités métriques, on caractérise les performances d'une méthode simple pour l'estimation de latences. On montre également qu'il est possible d'avoir des estimations exactes des débits, si le routage suit le chemin de débit maximal. Dans la troisième partie on propose et on analyse une méthode distribuée pour control de flux dans les réseaux pair-à-pair de live-streaming qui prend en compte les couts réseau. On montre qu'une telle approche est optimale dans le cas ou les pairs implémentent le Network Coding.
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Sidi, Bah Aladé Habib. "Distributed algorithms in autonomous and heterogeneous networks." Thesis, Avignon, 2012. http://www.theses.fr/2012AVIG0184/document.

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La diversité croissante des différents agents constituant les réseaux de communication actuels ainsi que la capacité accrue des technologies concurrentes dans l’environnement réseau a conduit à la prise en compte d’une nouvelle approche distribuée de la gestion du réseau. Dans cet environnement réseau évolué, le besoin en accroissement de la bande passante et en ressources rares, s’oppose à la réduction de la consommation énergétique globale.Dans notre travail nous nous intéressons à l’application de mécanismes distribués et de méthodes d’apprentissages visant à introduire d’avantage d’autonomie dans les réseaux hétérogènes, mobiles en particulier, tout en améliorant les performances par rapport aux débits et à la qualité de service. Notre étude se concentre principalement sur l’élaboration de mécanismes distribués stochastiques et énergétiquement efficaces en profitant des capacités de calcul de tous les agents et entités du réseau. Divers outils de la théorie des jeux nous permettent de modéliser et d’étudier différents types de systèmes dont la complexité est induite par la grande taille, l’hétérogénéité et le caractère dynamique des interconnexions. Plus spécifiquement, nous utilisons des outils d’apprentissage par renforcement pour aborder des questions telles que l’attachement distribué des utilisateurs permettant une gestion dynamique, décentralisée et efficace des ressources radio. Nous combinons ensuite les procédures de sélection d’accès à des méthodes d’optimisation distribuées du type gradient stochastique, pour adresser le problème de coordination des interférences intercellulaires (ICIC) dans les réseaux LTE-A. Cette approche se base sur un contrôle de puissance dynamique conduisant à une réutilisation fractionnaire des fréquences radios. Par ailleurs nous adressons dans les réseaux décentralisés non-hiérarchiques, plus précisément les réseaux tolérants aux délais (DTNs), des méthodes décentralisées liées à la minimisation du délai de transmission de bout en bout. Dans ce cadre nous nous intéressons, en outre des équilibres de Nash, à la notion d’équilibre évolutionnairement stables dans différents contextes de jeux évolutionnaires, jeux évolutionnaires décisionnels markoviens et jeux de minorité. Enfin, la majeure partie du travail effectué se rattachant aux tests et validations par simulations,nous présentons plusieurs éléments d’implémentations et d’intégrations liés à la mise en place de plateformes de simulations et d’expérimentations
Growing diversity of agents in current communication networks and increasing capacitiesof concurrent technologies in the network environment has lead to the considerationof a novel distributed approach of the network management. In this evolvednetwork environment the increasing need for bandwidth and rare channel resources,opposes to reduction of the total energy consumption.This thesis focuses on application of distributed mechanisms and learning methodsto allow for more autonomy in the heterogeneous network, this in order to improveits performances. We are mainly interested in energy efficient stochastic mechanismsthat will operate in a distributed fashion by taking advantage of the computationalcapabilities of all the agents and entities of the network. We rely on application ofGame theory to study different types of complex systems in the distributed wirelessnetworks with dynamic interconnectivity.Specifically, we use the stochastic reinforcement learning tools to address issuessuch as, distributed user-network association that allows achieving an efficient dynamicand decentralized radio resource management. Then, we combine access selectionprocedures with distributed optimization to address the inter-cells interferencescoordination (ICIC) for LTE-advanced networks using dynamic power control and designof fractional frequency reuse mechanisms. Moreover we address in non-hierarchicalnetworks, more precisely in Delay Tolerant Networks (DTNs), decentralized methodsrelated to minimization of the end-to-end communication delay. In this framework weare interested, in addition to Nash equilibrium, to the notion of evolutionary stableequiliria in the different context of Evolutionary Games, Markov Decision EvolutionaryGames and Minority Games. As the major parts of our work includes testing andvalidations by simulations, eventually we present several implementations and integrationsmaterials for edition of simulation platforms and test beds
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Xu, Songcen. "Distributed signal processing algorithms for wireless networks." Thesis, University of York, 2015. http://etheses.whiterose.ac.uk/9516/.

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Distributed signal processing algorithms have become a key approach for statistical inference in wireless networks and applications such as wireless sensor networks and smart grids. It is well known that distributed processing techniques deal with the extraction of information from data collected at nodes that are distributed over a geographic area. In this context, for each specific node, a set of neighbor nodes collect their local information and transmit the estimates to a specific node. Then, each specific node combines the collected information together with its local estimate to generate an improved estimate. In this thesis, novel distributed cooperative algorithms for inference in ad hoc, wireless sensor networks and smart grids are investigated. Low-complexity and effective algorithms to perform statistical inference in a distributed way are devised. A number of innovative approaches for dealing with node failures, compression of data and exchange of information are proposed and summarized as follows: Firstly, distributed adaptive algorithms based on the conjugate gradient (CG) method for distributed networks are presented. Both incremental and diffusion adaptive solutions are considered. Secondly, adaptive link selection algorithms for distributed estimation and their application to wireless sensor networks and smart grids are proposed. Thirdly, a novel distributed compressed estimation scheme is introduced for sparse signals and systems based on compressive sensing techniques. The proposed scheme consists of compression and decompression modules inspired by compressive sensing to perform distributed compressed estimation. A design procedure is also presented and an algorithm is developed to optimize measurement matrices. Lastly, a novel distributed reduced-rank scheme and adaptive algorithms are proposed for distributed estimation in wireless sensor networks and smart grids. The proposed distributed scheme is based on a transformation that performs dimensionality reduction at each agent of the network followed by a reduced–dimension parameter vector.
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Saia, Jared. "Algorithms for managing data in distributed systems /." Thesis, Connect to this title online; UW restricted, 2002. http://hdl.handle.net/1773/6941.

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Guillén, Alejandro. "Implementation of a Distributed Algorithm for Multi-camera Visual Feature Extraction in a Visual Sensor Network Testbed." Thesis, KTH, Kommunikationsnät, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-167415.

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Visual analysis tasks, like detection, recognition and tracking, are com- putationally intensive, and it is therefore challenging to perform such tasks in visual sensor networks, where nodes may be equipped with low power CPUs. A promising solution is to augment the sensor network with pro- cessing nodes, and to distribute the processing tasks among the process- ing nodes of the visual sensor network. The objective of this project is to enable a visual sensor network testbed to operate with multiple cam- era sensors, and to implement an algorithm that computes the allocation of the visual feature tasks to the processing nodes. In the implemented system, the processing nodes can receive and process data from differ- ent camera sensors simultaneously. The acquired images are divided into sub-images, the sizes of the sub-images are computed through solving a linear programming problem. The implemented algorithm performs local optimization in each camera sensor without data exchange with the other cameras in order to minimize the communication overhead and the data computational load of the camera sensors. The implementation work is performed on a testbed that consists of BeagleBone Black computers with IEEE 802.15.4 or IEEE 802.11 USB modules, and the existing code base is written in C++. The implementation is used to assess the performance of the distributed algorithm in terms of completion time. The results show a good performance providing lower average completion time.
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Books on the topic "Distributed algorithms for camera networks"

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Erciyes, K. Distributed Graph Algorithms for Computer Networks. London: Springer London, 2013. http://dx.doi.org/10.1007/978-1-4471-5173-9.

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Haddad, Serge. Distributed systems: Design and algorithms. Hoboken, NJ: John Wiley & Sons, 2011.

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Networks and distributed computation: Concepts, tools, and algorithms. Cambridge, Mass: MIT Press, 1988.

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Raynal, M. Networks and distributed computation: Concepts, tools and algorithms. London: North Oxford Academic, 1987.

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Raynal, Michel. Networks and distributed computation: Concepts, tools and algorithms. London: North Oxford Academic, 1987.

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Dembiński, Piotr. Distributed and always successful enumeration algorithm. Warszawa: Instytut Podstaw Informatyki Polskiej Akademii Nauk, 1996.

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Michael, Gastpar, ed. Distributed source coding: Theory, algorithms, and applications. Amsterdam: Academic Press, 2009.

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Bullo, Francesco. Distributed control of robotic networks: A mathematical approach to motion coordination algorithms. Princeton, N.J: Princeton University Press, 2009.

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International Conference on Distributed Computing Systems (19th 1999 Austin, Texas). Workshop on Self-Stabilizing Systems: 19th IEEE International Conference on Distributed Computing Systems : proceedings : May 31-June 4, 1999, Austin, Texas. Los Alamitos, California: IEEE Computer Society, 1999.

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Reisig, Wolfgang. Elements of Distributed Algorithms: Modeling and Analysis with Petri Nets. Berlin, Heidelberg: Springer Berlin Heidelberg, 1998.

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Book chapters on the topic "Distributed algorithms for camera networks"

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Tron, Roberto, Andreas Terzis, and René Vidal. "Distributed Consensus Algorithms for Image-Based Localization in Camera Sensor Networks." In Distributed Video Sensor Networks, 289–302. London: Springer London, 2011. http://dx.doi.org/10.1007/978-0-85729-127-1_20.

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Basso, Filippo, Riccardo Levorato, Matteo Munaro, and Emanuele Menegatti. "A Distributed Calibration Algorithm for Color and Range Camera Networks." In Studies in Computational Intelligence, 413–36. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-26054-9_16.

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Roy-Chowdhury, Amit K., and Bi Song. "Distributed Processing in Camera Networks." In Camera Networks, 33–57. Cham: Springer International Publishing, 2012. http://dx.doi.org/10.1007/978-3-031-01811-4_3.

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Barbosa, Valmir C. "Distributed Algorithms." In Handbook of Computer Networks, 286–97. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2012. http://dx.doi.org/10.1002/9781118256107.ch18.

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Chou, Ching-Tsun, Israel Cidon, Inder S. Gopal, and Shmuel Zaks. "Synchronizing asynchronous bounded delay networks." In Distributed Algorithms, 212–18. Berlin, Heidelberg: Springer Berlin Heidelberg, 1988. http://dx.doi.org/10.1007/bfb0019806.

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Jakoby, Andreas, and Rüdiger Reischuk. "Data transmission in processor networks." In Distributed Algorithms, 145–59. Berlin, Heidelberg: Springer Berlin Heidelberg, 1995. http://dx.doi.org/10.1007/bfb0022144.

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Beimell, Amos, and Matthew Franklin. "Reliable communication over partially authenticated networks." In Distributed Algorithms, 245–59. Berlin, Heidelberg: Springer Berlin Heidelberg, 1997. http://dx.doi.org/10.1007/bfb0030688.

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Dolev, Shlomi, and Jennifer L. Welch. "Crash resilient communication in dynamic networks." In Distributed Algorithms, 129–44. Berlin, Heidelberg: Springer Berlin Heidelberg, 1993. http://dx.doi.org/10.1007/3-540-57271-6_32.

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Baratz, Alan, Inder Gopal, and Adrian Segall. "Fault tolerant queries in computer networks." In Distributed Algorithms, 30–40. Berlin, Heidelberg: Springer Berlin Heidelberg, 1988. http://dx.doi.org/10.1007/bfb0019792.

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Lavallée, Ivan, and Christian Lavault. "Spanning tree construction for nameless networks." In Distributed Algorithms, 41–56. Berlin, Heidelberg: Springer Berlin Heidelberg, 1991. http://dx.doi.org/10.1007/3-540-54099-7_4.

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Conference papers on the topic "Distributed algorithms for camera networks"

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Eriksson, Emil, Gyorgy Dan, and Viktoria Fodor. "Algorithms for distributed feature extraction in multi-camera visual sensor networks." In 2015 IFIP Networking Conference (IFIP Networking). IEEE, 2015. http://dx.doi.org/10.1109/ifipnetworking.2015.7145333.

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Wittke, Michael, Alvaro del Amo Jimenez, Sascha Radike, Carsten Grenz, and Jorg Hahner. "ENRA: Event-based network reconfiguration algorithm for Active Camera Networks." In 2011 Fifth ACM/IEEE International Conference on Distributed Smart Cameras (ICDSC). IEEE, 2011. http://dx.doi.org/10.1109/icdsc.2011.6042936.

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Li, Chaoyang, and Anu G. Bourgeois. "Lifetime and Full-View Coverage Guarantees Through Distributed Algorithms in Camera Sensor Networks." In 2017 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW). IEEE, 2017. http://dx.doi.org/10.1109/ipdpsw.2017.57.

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Xiaoqin Wang, Y. Ahmet Sekercioglu, and Tom Drummond. "A real-time distributed relative pose estimation algorithm for RGB-D camera equipped visual sensor networks." In 2013 Seventh International Conference on Distributed Smart Cameras (ICDSC). IEEE, 2013. http://dx.doi.org/10.1109/icdsc.2013.6778208.

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Navin, Ahmad Habibizad, and Mir Kamal Mirnia. "Solving coverage problem in wireless camera-based sensor networks by using a distributed evolutionary algorithm." In 2014 5th IEEE International Conference on Software Engineering and Service Science (ICSESS). IEEE, 2014. http://dx.doi.org/10.1109/icsess.2014.6933752.

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Elhamifar, Ehsan, and Rene Vidal. "Distributed calibration of Camera Sensor Networks." In 2009 Third ACM/IEEE International Conference on Distributed Smart Cameras (ICDSC). IEEE, 2009. http://dx.doi.org/10.1109/icdsc.2009.5289397.

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Borra, Domenica, and Fabio Fagnani. "Asynchronous distributed calibration of camera networks." In 2013 European Control Conference (ECC). IEEE, 2013. http://dx.doi.org/10.23919/ecc.2013.6669757.

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Esterle, Lukas, Peter R. Lewis, Richie McBride, and Xin Yao. "The Future of Camera Networks." In ICDSC 2017: International Conference on Distributed Smart Cameras. New York, NY, USA: ACM, 2017. http://dx.doi.org/10.1145/3131885.3131931.

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Barton-Sweeney, Andrew, Dimitrios Lymberopoulos, and Andreas Savvides. "Sensor Localization and Camera Calibration in Distributed Camera Sensor Networks." In 2006 3rd International Conference on Broadband Communications, Networks and Systems. IEEE, 2006. http://dx.doi.org/10.1109/broadnets.2006.4374301.

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Jiuqing, Wan, and Liu Qingyun. "Distributed data association in smart camera networks." In 2011 Fifth ACM/IEEE International Conference on Distributed Smart Cameras (ICDSC). IEEE, 2011. http://dx.doi.org/10.1109/icdsc.2011.6042907.

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Reports on the topic "Distributed algorithms for camera networks"

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Lobaton, Edgar J., Parvez Ahammad, and S. S. Sastry. Algebraic Approach for Recovering Topology in Distributed Camera Networks. Fort Belvoir, VA: Defense Technical Information Center, January 2009. http://dx.doi.org/10.21236/ada538850.

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Gidas, Basilis, and Sumit Ghosh. Algorithms for Image Compression, Distributed Communication Networks and Distributed Resource Allocation. Fort Belvoir, VA: Defense Technical Information Center, September 1998. http://dx.doi.org/10.21236/ada357863.

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Serpedin, Erchin. High-Performance Clock Synchronization Algorithms for Distributed Wireless Airborne Computer Networks with Applications to Localization and Tracking of Targets. Fort Belvoir, VA: Defense Technical Information Center, June 2010. http://dx.doi.org/10.21236/ada523331.

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