Title :
Particle filters for multi-face detection and tracking with automatic clustering
Author :
Stasiak, Lukasz ; Pacut, Andrzej
Author_Institution :
Warsaw Univ. of Technol., Warsaw
Abstract :
We develop a systems that detects and track individuals and groups of people in real-time, designed as a first screening of the iris-based access control. We use particle filtering in the conditional density propagation framework of hard and Blake, and base the face detection on the skin color in HSV colorspace. Particle assignment to faces is done automatically the use of X-Means algorithm. The X-means algorithm is modified to (1) avoid the local extrema (2) to deal better with odd number of clusters. The modified algorithm is fast enough to work in real time and outperforms its original version.
Keywords :
Monte Carlo methods; access control; face recognition; image colour analysis; particle filtering (numerical methods); pattern clustering; tracking filters; Monte Carlo filtering; X-Means algorithm; automatic clustering; conditional density propagation framework; iris-based access control; multiface detection; particle filtering; skin color; tracking; Access control; Clustering algorithms; Computer networks; Face detection; Filtering; Monte Carlo methods; Particle filters; Particle tracking; Probability distribution; Real time systems; Condensation; X-Means; automatic clustering; face tracking; particle filters;
Conference_Titel :
Imaging Systems and Techniques, 2007. IST '07. IEEE International Workshop on
Conference_Location :
Krakow
Print_ISBN :
1-4244-0965-9
Electronic_ISBN :
1-4244-0965-9
DOI :
10.1109/IST.2007.379594