Neural Network-Based Face Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Example-Based Learning for View-Based Human Face Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
CONDENSATION—Conditional Density Propagation forVisual Tracking
International Journal of Computer Vision
A survey of computer vision-based human motion capture
Computer Vision and Image Understanding - Modeling people toward vision-based underatanding of a person's shape, appearance, and movement
Detecting Faces in Images: A Survey
IEEE Transactions on Pattern Analysis and Machine Intelligence
Non-intrusive Person Authentication for Access Control by Visual Tracking and Face Recognition
AVBPA '97 Proceedings of the First International Conference on Audio- and Video-Based Biometric Person Authentication
Handbook of Face Recognition
AdaBoost Tracker Embedded in Adaptive Particle Filtering
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 04
Journal of Cognitive Neuroscience
Robust visual tracking for multiple targets
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part IV
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A system for parallel face detection, tracking and recognition in real-time video sequences is being developed. The particle filtering is utilized for the purpose of combined and effective detection, tracking and recognition. Temporal information contained in videos is utilized. Fast, skin color-based face extraction and normalization technique is applied. Consequently, real-time processing is achieved. Implementation of face recognition mechanisms within the tracking framework is used not only for the purpose of identity recognition, but also to improve the tracking robustness in case of multi-person tracking scenarios. In such scenarios, face-to-track assignment conflicts can often be resolved with the use of motion modeling. However, in case of close trajectories, motion-based conflict resolution can be erroneous. Identity clue can be used to improve tracking quality in such cases. This paper describes the concept of face tracking corrections with the use of identity recognition mechanism, implemented within a compact particle filtering-based framework for face detection, tracking and recognition.