Probabilistic recognition of human faces from video
Computer Vision and Image Understanding - Special issue on Face recognition
Supporting timeliness and accuracy in distributed real-time content-based video analysis
MULTIMEDIA '03 Proceedings of the eleventh ACM international conference on Multimedia
Parallel hypothesis driven video content analysis
Proceedings of the 2004 ACM symposium on Applied computing
Real-time surveillance video display with salience
Proceedings of the third ACM international workshop on Video surveillance & sensor networks
Real-time video content analysis: QoS-aware application composition and parallel processing
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
Real time face authentication system using autoassociative neural network models
ICME '03 Proceedings of the 2003 International Conference on Multimedia and Expo - Volume 2
EURASIP Journal on Advances in Signal Processing
Object recognition and segmentation in videos by connecting heterogeneous visual features
Computer Vision and Image Understanding
Facial expression recognition - A real time approach
Expert Systems with Applications: An International Journal
Person recognition using facial video information: A state of the art
Journal of Visual Languages and Computing
Audio-guided video-based face recognition
IEEE Transactions on Circuits and Systems for Video Technology
Automatic pedestrian detection and tracking for real-time video surveillance
AVBPA'03 Proceedings of the 4th international conference on Audio- and video-based biometric person authentication
Person recognition using human head motion information
AMDO'06 Proceedings of the 4th international conference on Articulated Motion and Deformable Objects
Face recognition using more than one still image: what is more?
SINOBIOMETRICS'04 Proceedings of the 5th Chinese conference on Advances in Biometric Person Authentication
Road Traffic Parameters Estimation by Dynamic Scene Analysis: A Systematic Review
International Journal of Grid and High Performance Computing
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A generic approach to simultaneous tracking and verification in video data is presented. The approach is based on posterior density estimation using sequential Monte Carlo methods. Visual tracking, which is in essence a temporal correspondence problem, is solved through probability density propagation, with the density being defined over a proper state space characterizing the object configuration. Verification is realized through hypothesis testing using the estimated posterior density. In its most basic form, verification can be performed as follows. Given a measurement vector Z and two hypotheses H1 and H0, we first estimate posterior probabilities P(H0|Z) and P(H1|Z), and then choose the one with the larger posterior probability as the true hypothesis. Several applications of the approach are illustrated by experiments devised to evaluate its performance. The idea is first tested on synthetic data, and then experiments with real video sequences are presented, illustrating vehicle tracking and verification, human (face) tracking and verification, facial feature tracking, and image sequence stabilization.