Face Recognition: Features Versus Templates
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Bayesian Framework for Robust Human Detection and Occlusion Handling using Human Shape Model
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 2 - Volume 02
AVSS '08 Proceedings of the 2008 IEEE Fifth International Conference on Advanced Video and Signal Based Surveillance
Passive sensor based dynamic object association with particle filtering
AVSS '07 Proceedings of the 2007 IEEE Conference on Advanced Video and Signal Based Surveillance
People tracking with anonymous and ID-sensors using Rao-Blackwellised particle filters
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
Face detection using quantized skin color regions merging andwavelet packet analysis
IEEE Transactions on Multimedia
Mutual calibration of camera motes and RFIDs for people localization and identification
Proceedings of the Fourth ACM/IEEE International Conference on Distributed Smart Cameras
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In this paper, we present an approach for providing dynamic object association and identification in heterogeneous sensor networks where identification sensors have coverage uncertainty. Detection uncertainty of identifications by the coverage uncertainty is managed by grouping unassociated identifications. In the system, visual sensors find corresponding objects between cameras by using homographic lines and track them by using multi-camera localization scheme. Identification sensors (i.e., RFID system, fingerprint or iris recognition system) are incorporated into the tracking system for objects identification. This paper elaborates possible identification cases and necessary conditions with the coverage uncertainty of identification sensors. Finally, the proposed association method is evaluated with a realistic simulation.