Exploiting the architecture of dynamic systems
AAAI '99/IAAI '99 Proceedings of the sixteenth national conference on Artificial intelligence and the eleventh Innovative applications of artificial intelligence conference innovative applications of artificial intelligence
Dynamic bayesian networks: representation, inference and learning
Dynamic bayesian networks: representation, inference and learning
Robust probabilistic inference in distributed systems
UAI '04 Proceedings of the 20th conference on Uncertainty in artificial intelligence
Distributed localization of networked cameras
Proceedings of the 5th international conference on Information processing in sensor networks
A robust architecture for distributed inference in sensor networks
IPSN '05 Proceedings of the 4th international symposium on Information processing in sensor networks
ACM Computing Surveys (CSUR)
Distributed consensus and linear functional calculation in networks: an observability perspective
Proceedings of the 6th international conference on Information processing in sensor networks
Robust message-passing for statistical inference in sensor networks
Proceedings of the 6th international conference on Information processing in sensor networks
EURASIP Journal on Applied Signal Processing
Computer Vision and Image Understanding
Belief Propagation in Wireless Sensor Networks - A Practical Approach
WASA '08 Proceedings of the Third International Conference on Wireless Algorithms, Systems, and Applications
Tracking many objects with many sensors
IJCAI'99 Proceedings of the 16th international joint conference on Artificial intelligence - Volume 2
Distributed visual-target-surveillance system in wireless sensor networks
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
3-D target-based distributed smart camera network localization
IEEE Transactions on Image Processing - Special section on distributed camera networks: sensing, processing, communication, and implementation
Tracking and activity recognition through consensus in distributed camera networks
IEEE Transactions on Image Processing - Special section on distributed camera networks: sensing, processing, communication, and implementation
Activity based matching in distributed camera networks
IEEE Transactions on Image Processing - Special section on distributed camera networks: sensing, processing, communication, and implementation
Inter-camera association of multi-target tracks by on-line learned appearance affinity models
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part I
Vehicle trajectory estimation using spatio-temporal MCMC
EURASIP Journal on Advances in Signal Processing - Special issue on advanced image processing for defense and security applications
Tractable inference for complex stochastic processes
UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part II
Distributed EM algorithms for density estimation and clustering in sensor networks
IEEE Transactions on Signal Processing
Data association based on optimization in graphical models with application to sensor networks
Mathematical and Computer Modelling: An International Journal
MAP estimation via agreement on trees: message-passing and linear programming
IEEE Transactions on Information Theory
Nonparametric belief propagation for self-localization of sensor networks
IEEE Journal on Selected Areas in Communications
Distributed EM Algorithm for Gaussian Mixtures in Sensor Networks
IEEE Transactions on Neural Networks
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One of the fundamental requirements for visual surveillance with smart camera networks is the correct association of camera's observations with the tracks of objects under tracking. Most of the current systems work in a centralized manner in that the observations on all cameras need to be transmitted to a central server where some data association algorithm is running. Recently some works have been shown for distributed data association based solely on appearance observation. However, how to perform distributed association inference using both appearance and spatio-temporal information is still unclear. In this article, we present a novel method for estimating the posterior distribution of the label of each observation, indicating which of the objects it comes from, based on belief propagation between neighboring cameras. We develop distributed forward and backward inference algorithms for online and offline application, respectively, and further extend the algorithms to the case of unreliable detection. We also incorporate the proposed inference algorithms into distributed EM framework to simultaneously solve the problem of data association and appearance model learning in a completely distributed manner. The proposed method is verified on artificial data and on real world observations collected by a camera networks in an office building.