Identity Recognition-Based Correction Mechanism for Face Tracking

摘要

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.