Title :
A unified probabilistic approach to face detection and tracking
Author :
Tao, Ji ; Tan, Yap-Peng
Author_Institution :
Sch. of Electr. & Electron. Eng., Nanyang Technol. Univ., Singapore
Abstract :
In this paper, we present a novel probabilistic approach to detecting and tracking human faces in video sequences. Specifically, with the use of multimodal observations a graphical chain model integrating smooth regularization is proposed. Using this model, the recovery of faces that are not detected or detected with only low confidence by a frame-based detector can be formulated as an overall optimization problem constrained by a set of reference faces, which are initially detected with high certainties. Experimental results demonstrate the effectiveness of our approach.
Keywords :
face recognition; image sequences; optimisation; surveillance; target tracking; video signal processing; detection certainty; detection confidence; face detection; face recovery; face tracking; frame-based detector; graphical chain model; human faces; multimodal observations; overall optimization problem; reference faces; smooth regularization integration; unified probabilistic approach; video sequences; Constraint optimization; Detectors; Event detection; Face detection; Humans; Indexing; Monitoring; Motion detection; Surveillance; Video sequences;
Conference_Titel :
Circuits and Systems, 2005. ISCAS 2005. IEEE International Symposium on
Print_ISBN :
0-7803-8834-8
DOI :
10.1109/ISCAS.2005.1465457