Thematische Bibliographien / Multi-Camera network

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Auswahl der wissenschaftlichen Literatur zum Thema „Multi-Camera network“

Autor: Grafiati

Veröffentlicht am 25. Mai 2024

Zuletzt aktualisiert am 31. Juli 2025

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Zeitschriftenartikel zum Thema "Multi-Camera network"

Wu, Yi-Chang, Ching-Han Chen, Yao-Te Chiu, and Pi-Wei Chen. "Cooperative People Tracking by Distributed Cameras Network." Electronics 10, no. 15 (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

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R.Kennady, Et al. "A Nonoverlapping Vision Field Multi-Camera Network for Tracking Human Build Targets." International Journal on Recent and Innovation Trends in Computing and Communication 11, no. 3 (2023): 366–69. http://dx.doi.org/10.17762/ijritcc.v11i3.9871.

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This research presents a procedure for tracking human build targets in a multi-camera network with nonoverlapping vision fields. The proposed approach consists of three main steps: single-camera target detection, single-camera target tracking, and multi-camera target association and continuous tracking. The multi-camera target association includes target characteristic extraction and the establishment of topological relations. Target characteristics are extracted based on the HSV (Hue, Saturation, and Value) values of each human build movement target, and the space-time topological relations o

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Sharma, Anil, Saket Anand, and Sanjit K. Kaul. "Reinforcement Learning Based Querying in Camera Networks for Efficient Target Tracking." Proceedings of the International Conference on Automated Planning and Scheduling 29 (May 25, 2021): 555–63. http://dx.doi.org/10.1609/icaps.v29i1.3522.

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Surveillance camera networks are a useful monitoring infrastructure that can be used for various visual analytics applications, where high-level inferences and predictions could be made based on target tracking across the network. Most multi-camera tracking works focus on re-identification problems and trajectory association problems. However, as camera networks grow in size, the volume of data generated is humongous, and scalable processing of this data is imperative for deploying practical solutions. In this paper, we address the largely overlooked problem of scheduling cameras for processin

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Zhao, Guoliang, Yuxun Zhou, Zhanbo Xu, Yadong Zhou, and Jiang Wu. "Hierarchical Multi-Supervision Multi-Interaction Graph Attention Network for Multi-Camera Pedestrian Trajectory Prediction." Proceedings of the AAAI Conference on Artificial Intelligence 36, no. 4 (2022): 4698–706. http://dx.doi.org/10.1609/aaai.v36i4.20395.

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Pedestrian trajectory prediction has become an essential underpinning in various human-centric applications including but not limited to autonomous vehicles, intelligent surveillance system and social robotics. Previous research endeavors mainly focus on single camera trajectory prediction (SCTP), while the problem of multi-camera trajectory prediction (MCTP) is often overly simplified into predicting presence in the next camera. This paper addresses MCTP from a more realistic yet challenging perspective, by redefining the task as a joint estimation of both future destination and possible traj

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Liu, Xin, Herman G. J. Groot, Egor Bondarev, and Peter H. N. de With. "Introducing Scene Understanding to Person Re-Identification using a Spatio-Temporal Multi-Camera Model." Electronic Imaging 2020, no. 10 (2020): 95–1. http://dx.doi.org/10.2352/issn.2470-1173.2020.10.ipas-095.

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In this paper, we investigate person re-identification (re-ID) in a multi-camera network for surveillance applications. To this end, we create a Spatio-Temporal Multi-Camera model (ST-MC model), which exploits statistical data on a person’s entry/exit points in the multi-camera network, to predict in which camera view a person will re-appear. The created ST-MC model is used as a novel extension to the Multiple Granularity Network (MGN) [1], which is the current state of the art in person re-ID. Compared to existing approaches that are solely based on Convolutional Neural Networks (CNNs), our a

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Li, Xiaolin, Wenhui Dong, Faliang Chang, and Peishu Qu. "Topology Learning of Non-overlapping Multi-camera Network." International Journal of Signal Processing, Image Processing and Pattern Recognition 8, no. 11 (2015): 243–54. http://dx.doi.org/10.14257/ijsip.2015.8.11.22.

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He, Li, Guoliang Liu, Guohui Tian, Jianhua Zhang, and Ze Ji. "Efficient Multi-View Multi-Target Tracking Using a Distributed Camera Network." IEEE Sensors Journal 20, no. 4 (2020): 2056–63. http://dx.doi.org/10.1109/jsen.2019.2949385.

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Li, Yun-Lun, Hao-Ting Li, and Chen-Kuo Chiang. "Multi-Camera Vehicle Tracking Based on Deep Tracklet Similarity Network." Electronics 11, no. 7 (2022): 1008. http://dx.doi.org/10.3390/electronics11071008.

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Multi-camera vehicle tracking at the city scale has received lots of attention in the last few years. It has large-scale differences, frequent occlusion, and appearance differences caused by the viewing angle differences, which is quite challenging. In this research, we propose the Tracklet Similarity Network (TSN) for a multi-target multi-camera (MTMC) vehicle tracking system based on the evaluation of the similarity between vehicle tracklets. In addition, a novel component, Candidates Intersection Ratio (CIR), is proposed to refine the similarity. It provides an associate scheme to build the

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Truong, Philips, Deligiannis, Abrahamyan, and Guan. "Automatic Multi-Camera Extrinsic Parameter Calibration Based on Pedestrian Torsors †." Sensors 19, no. 22 (2019): 4989. http://dx.doi.org/10.3390/s19224989.

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Extrinsic camera calibration is essential for any computer vision task in a camera network. Typically, researchers place a calibration object in the scene to calibrate all the cameras in a camera network. However, when installing cameras in the field, this approach can be costly and impractical, especially when recalibration is needed. This paper proposes a novel, accurate and fully automatic extrinsic calibration framework for camera networks with partially overlapping views. The proposed method considers the pedestrians in the observed scene as the calibration objects and analyzes the pedest

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Guan, Banglei, Xiangyi Sun, Yang Shang, Xiaohu Zhang, and Manuel Hofer. "Multi-camera networks for motion parameter estimation of an aircraft." International Journal of Advanced Robotic Systems 14, no. 1 (2017): 172988141769231. http://dx.doi.org/10.1177/1729881417692312.

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A multi-camera network is proposed to estimate an aircraft’s motion parameters relative to the reference platform in large outdoor fields. Multiple cameras are arranged to cover the aircraft’s large-scale motion spaces by field stitching. A camera calibration method using dynamic control points created by a multirotor unmanned aerial vehicle is presented under the conditions that the field of view of the cameras is void. The relative deformation of the camera network caused by external environmental factors is measured and compensated using a combination of cameras and laser rangefinders. A se

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Dissertationen zum Thema "Multi-Camera network"

Zhao, Jian. "Camera Planning and Fusion in a Heterogeneous Camera Network." UKnowledge, 2011. http://uknowledge.uky.edu/ece_etds/2.

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Wide-area camera networks are becoming more and more common. They have widerange of commercial and military applications from video surveillance to smart home and from traffic monitoring to anti-terrorism. The design of such a camera network is a challenging problem due to the complexity of the environment, self and mutual occlusion of moving objects, diverse sensor properties and a myriad of performance metrics for different applications. In this dissertation, we consider two such challenges: camera planing and camera fusion. Camera planning is to determine the optimal number and placement of

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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 feat

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Jeong, Kideog. "OBJECT MATCHING IN DISJOINT CAMERAS USING A COLOR TRANSFER APPROACH." UKnowledge, 2007. http://uknowledge.uky.edu/gradschool_theses/434.

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Object appearance models are a consequence of illumination, viewing direction, camera intrinsics, and other conditions that are specific to a particular camera. As a result, a model acquired in one view is often inappropriate for use in other viewpoints. In this work we treat this appearance model distortion between two non-overlapping cameras as one in which some unknown color transfer function warps a known appearance model from one view to another. We demonstrate how to recover this function in the case where the distortion function is approximated as general affine and object appearance is

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Macknojia, Rizwan. "Design and Calibration of a Network of RGB-D Sensors for Robotic Applications over Large Workspaces." Thèse, Université d'Ottawa / University of Ottawa, 2013. http://hdl.handle.net/10393/23976.

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This thesis presents an approach for configuring and calibrating a network of RGB-D sensors used to guide a robotic arm to interact with objects that get rapidly modeled in 3D. The system is based on Microsoft Kinect sensors for 3D data acquisition. The work presented here also details an analysis and experimental study of the Kinect’s depth sensor capabilities and performance. The study comprises examination of the resolution, quantization error, and random distribution of depth data. In addition, the effects of color and reflectance characteristics of an object are also analyzed. The study e

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Chen, Huiqin. "Registration of egocentric views for collaborative localization in security applications." Electronic Thesis or Diss., université Paris-Saclay, 2021. http://www.theses.fr/2021UPASG031.

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Cette thèse s’intéresse à la localisation collaborative à partir d’une caméra mobile et d’une caméra statique pour des applications de vidéo-surveillance. Pour la surveillance d’évènements sensibles, la sécurité civile recours de plus en plus à des réseaux de caméras collaboratives incluant des caméras dynamiques et des caméras de surveillance traditionnelles, statiques. Il s’agit, dans des scènes de foules, de localiser d’une part le porteur de la caméra (typiquement agent de sécurité) mais également des évènements observés dans les images, afin de guider les secours par exemple. Cependant, l

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Konda, Krishna Reddy. "Dynamic Camera Positioning and Reconfiguration for Multi-Camera Networks." Doctoral thesis, Università degli studi di Trento, 2015. https://hdl.handle.net/11572/367752.

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The large availability of different types of cameras and lenses, together with the reduction in price of video sensors, has contributed to a widespread use of video surveillance systems, which have become a widely adopted tool to enforce security and safety, in detecting and preventing crimes and dangerous events. The possibility for personalization of such systems is generally very high, letting the user customize the sensing infrastructure, and deploying ad-hoc solutions based on the current needs, by choosing the type and number of sensors, as well as by adjusting the different camera param

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Konda, Krishna Reddy. "Dynamic Camera Positioning and Reconfiguration for Multi-Camera Networks." Doctoral thesis, University of Trento, 2015. http://eprints-phd.biblio.unitn.it/1386/1/PhD-Thesis.pdf.

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Dziri, Aziz. "Suivi visuel d'objets dans un réseau de caméras intelligentes embarquées." Thesis, Clermont-Ferrand 2, 2015. http://www.theses.fr/2015CLF22610/document.

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Le suivi d’objets est de plus en plus utilisé dans les applications de vision par ordinateur. Compte tenu des exigences des applications en termes de performance, du temps de traitement, de la consommation d’énergie et de la facilité du déploiement des systèmes de suivi, l’utilisation des architectures embarquées de calcul devient primordiale. Dans cette thèse, nous avons conçu un système de suivi d’objets pouvant fonctionner en temps réel sur une caméra intelligente de faible coût et de faible consommation équipée d’un processeur embarqué ayant une architecture légère en ressources de calcul.

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Tahir, Syed Fahad. "Resource-constrained re-identification in camera networks." Thesis, Queen Mary, University of London, 2016. http://qmro.qmul.ac.uk/xmlui/handle/123456789/36123.

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In multi-camera surveillance, association of people detected in different camera views over time, known as person re-identification, is a fundamental task. Re-identification is a challenging problem because of changes in the appearance of people under varying camera conditions. Existing approaches focus on improving the re-identification accuracy, while no specific effort has yet been put into efficiently utilising the available resources that are normally limited in a camera network, such as storage, computation and communication capabilities. In this thesis, we aim to perform and improve the

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Yildiz, Enes. "PROVIDING MULTI-PERSPECTIVE COVERAGE IN WIRELESS MULTIMEDIA SENSOR NETWORKS." OpenSIUC, 2011. https://opensiuc.lib.siu.edu/theses/717.

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Deployment of cameras in Wireless Multimedia Sensor Networks (WMSNs) is crucial in achieving good coverage, accuracy and fault tolerance. With the decreased costs of wireless cameras, WMSNs provide opportunities for redundant camera deployment in order to get multiple disparate views of events. Referred to as multi-perspective coverage (MPC), this thesis proposes an optimal solution for camera deployment that can achieve full MPC for a given region. The solution is based on a Bi-Level mixed integer program (MIP) which works by solving two sub-problems named master and sub-problems. The master

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Bücher zum Thema "Multi-Camera network"

K, Aghajan Hamid, Cavallaro Andrea, and ScienceDirect (Online service), eds. Multi-camera networks: Principles and applications. Elsevier, AP, 2009.

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Multi-Camera Networks. Elsevier, 2009. http://dx.doi.org/10.1016/b978-0-12-374633-7.x0001-8.

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Cavallaro, Andrea, and Hamid Aghajan. Multi-Camera Networks: Principles and Applications. Elsevier Science & Technology Books, 2009.

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Beach, David Michael. Multi-camera benchmark localization for mobile robot networks. 2004.

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Beach, David Michael. Multi-camera benchmark localization for mobile robot networks. 2005.

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Rawlinson, Jules. A Requiem for Edward Snowden. University of Edinburgh, 2024. http://dx.doi.org/10.2218/ed.9781836450566.

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A Requiem for Edward Snowden is a 50-minute audio-visual work by Matthew Collings and Jules Rawlinson which addresses surveillance, data privacy, loss of faith, moral choice, and personal sacrifice in an environment where we are totally reliant on electronic communication and daily routines; and in which our privacy is routinely compromised. The work is performed by a chamber trio comprising violin, cello and clarinet, with live electronics and live visuals. The work is multi-layered and textured, both sonically and visually, and includes computer generated, fixed-media and live captured image

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Buchteile zum Thema "Multi-Camera network"

Koyama, Takashi, and Yusuke Gotoh. "Multi-camera Live Video Streaming over Wireless Network." In Advances in Mobile Computing and Multimedia Intelligence. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-48348-6_12.

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Xing, Chang, Sichen Bai, Yi Zhou, Zhong Zhou, and Wei Wu. "Coarse-to-Fine Multi-camera Network Topology Estimation." In Advances in Multimedia Information Processing – PCM 2017. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-77383-4_96.

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Bo Bo, Nyan, Maarten Slembrouck, Peter Veelaert, and Wilfried Philips. "Distributed Multi-class Road User Tracking in Multi-camera Network For Smart Traffic Applications." In Advanced Concepts for Intelligent Vision Systems. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-40605-9_44.

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Mavrinac, Aaron, Jose Luis Alarcon Herrera, and Xiang Chen. "Evaluating the Fuzzy Coverage Model for 3D Multi-camera Network Applications." In Intelligent Robotics and Applications. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-16584-9_66.

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Choudhary, Ayesha, Shubham Sharma, Indu Sreedevi, and Santanu Chaudhury. "Real-Time Distributed Multi-object Tracking in a PTZ Camera Network." In Lecture Notes in Computer Science. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-19941-2_18.

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Peng, Zhihao, Xinyuan Qi, Sheng Wu, Jianga Shang, and Linquan Yang. "Multi-scale Traffic Camera Image Detection Network Based on Improved YOLOv8." In Lecture Notes in Computer Science. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-96-0125-7_8.

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Chen, Xiaotang, Kaiqi Huang, and Tieniu Tan. "Learning the Three Factors of a Non-overlapping Multi-camera Network Topology." In Communications in Computer and Information Science. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-33506-8_14.

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Shang, Yang, Qifeng Yu, Yong Xu, et al. "An Innovative Multi-headed Camera Network: A Displacement-Relay Videometrics Method in Unstable Areas." In Fringe 2013. Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-642-36359-7_161.

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Chen, Aofei, Lian Tong, Zhiqiang Wen, Yifan Hu, and Lini Wu. "Camera Source Identification for Online Social Network Images Based on Multi-scale Feature Fusion." In Communications in Computer and Information Science. Springer Nature Singapore, 2025. https://doi.org/10.1007/978-981-96-9949-0_18.

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Tran, Quang Khoi, Khanh Hieu Ngo, Anh Huy Le Dinh, Lu Tien Truong, Hai Quan Tran, and Anh Tuan Trinh. "Development of a Real-Time Obstacle Detection System on Embedded Computer Based on Neural Network and Multi-camera Streaming." In Intelligent Systems and Networks. Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-3394-3_35.

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Konferenzberichte zum Thema "Multi-Camera network"

Zhang, Jinkai, Zijuan Han, Yunxia Liu, and Yang Yang. "A Multi-Domain Camera Model Identification Feature Restoration Network to Counter AI Compression Attacks." In 2024 Asia Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC). IEEE, 2024. https://doi.org/10.1109/apsipaasc63619.2025.10848864.

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Wang, Rongxin, Ronghai Chen, Meng Yang, and Xuguang Lan. "Multi-modal Camera and One-beam LiDAR Fusion Network for Low-cost 3D Object Detection." In 2024 IEEE International Conference on Robotics and Biomimetics (ROBIO). IEEE, 2024. https://doi.org/10.1109/robio64047.2024.10907410.

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Liu, Wenyue, Denise Koh Choon Lian, Zhihao Zhang, and Jianguo Qiu. "LFEMSFF: A Basketball Posture Detection Model Combining Local Feature Enhancement and Multi-Camera Spatio-Temporal Feature Fusion." In 2024 6th International Conference on Electronics and Communication, Network and Computer Technology (ECNCT). IEEE, 2024. http://dx.doi.org/10.1109/ecnct63103.2024.10704235.

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Bai, Wenfeng, Haitao Luo, Xiankang Yu, et al. "An Automatic Intrinsic and Extrinsic Calibration Method for Multi-Camera Systems Without a Common Field of View Under Weak Observation Conditions Based on Total-Station-Assisted Point Localization." In 2025 2nd International Conference on Algorithms, Software Engineering and Network Security (ASENS). IEEE, 2025. https://doi.org/10.1109/asens64990.2025.11011116.

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Fan, Xiaotong, and Huicheng Zheng. "An Instance-Level Motion-Aware Graph Model for Multi-target Multi-camera Tracking." In 2024 International Joint Conference on Neural Networks (IJCNN). IEEE, 2024. http://dx.doi.org/10.1109/ijcnn60899.2024.10650328.

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Chang, I.-Cheng, Jia-Hong Yang, and Yi-Hsiang Liao. "Multi-Camera Based Social Network Analysis." In 2012 Eighth International Conference on Intelligent Information Hiding and Multimedia Signal Processing (IIH-MSP). IEEE, 2012. http://dx.doi.org/10.1109/iih-msp.2012.48.

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Gao, Yi, Wanneng Wu, Ao Liu, Qiaokang Liang, and Jianwen Hu. "Multi-Target Multi-Camera Tracking with Spatial-Temporal Network." In 2023 7th International Symposium on Computer Science and Intelligent Control (ISCSIC). IEEE, 2023. http://dx.doi.org/10.1109/iscsic60498.2023.00048.

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Ganti, Raghu, Mudhakar Srivatsa, and B. S. Manjunath. "Entity reconciliation in a multi-camera network." In ICDCN '16: 17th International Conference on Distributed Computing and Networking. ACM, 2016. http://dx.doi.org/10.1145/2833312.2849566.

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Mhiri, Rawia, Hichem Maiza, Stephane Mousset, Khaled Taouil, Pascal Vasseur, and Abdelaziz Bensrhair. "Obstacle detection using unsynchronized multi-camera network." In 2015 12th International Conference on Ubiquitous Robots and Ambient Intelligence (URAI). IEEE, 2015. http://dx.doi.org/10.1109/urai.2015.7358917.

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Peng, Peixi, Yonghong Tian, Yaowei Wang, and Tiejun Huang. "Multi-camera Pedestrian Detection with Multi-view Bayesian Network Model." In British Machine Vision Conference 2012. British Machine Vision Association, 2012. http://dx.doi.org/10.5244/c.26.69.

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