loading...
Face Tracking by Maximizing Classification Score of Face Detector Based on Rectangle Features
New York, New York January 04-January 07
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICVS.2006.27Fourth IEEE International Conference ...
 This Article 
 
PDF
HTML
 
 Share 
   
 Bibliographic References 
   
 Add to: 
 
Digg
Furl
Spurl
Blink
Simpy
Google
Del.icio.us
Y!MyWeb
 
 Search 
   
Akinori HIDAKA, University of Tsukuba, Japan
Kenji NISHIDA, Industrial Science and Technology (AIST), Japan
Takio KURITA, Industrial Science and Technology (AIST), Japan
Face tracking continues to be an important topic in computer vision. We describe a tracking algorithm based on a static face detector. Our face detector is a rectanglefeature- based boosted classifier, which outputs the confidence whether an input image is a face. The function that outputs this confidence, called a score function, contains important information about the location of a moving target. A target that has moved will be located in the gradient direction of a score function from the location before moving. Therefore, our tracker will go to the region where the score is maximum using gradient information of this function. We show that this algorithm works by the combination of jumping to the gradient direction and precise search at the local region.
Citation:
Akinori HIDAKA, Kenji NISHIDA, Takio KURITA, "Face Tracking by Maximizing Classification Score of Face Detector Based on Rectangle Features," icvs, pp.48, Fourth IEEE International Conference on Computer Vision Systems (ICVS'06), 2006
Usage of this product signifies your acceptance of the Terms of Use.


Suggestions