DocumentCode
2920168
Title
Particle filters for multi-face detection and tracking with automatic clustering
Author
Stasiak, Lukasz ; Pacut, Andrzej
Author_Institution
Warsaw Univ. of Technol., Warsaw
fYear
2007
fDate
5-5 May 2007
Firstpage
1
Lastpage
6
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;
fLanguage
English
Publisher
ieee
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
Type
conf
DOI
10.1109/IST.2007.379594
Filename
4258794
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