Title :
The SVM-Minus Similarity Score for Video Face Recognition
Author :
Wolf, Lars ; Levy, Noga
Author_Institution :
Blavatnik Sch. of Comput. Sci., Tel-Aviv Univ., Tel-Aviv, Israel
Abstract :
Challenge, but also an opportunity to eliminate spurious similarities. Luckily, a major source of confusion in visual similarity of faces is the 3D head orientation, for which image analysis tools provide an accurate estimation. The method we propose belongs to a family of classifier-based similarity scores. We present an effective way to discount pose induced similarities within such a framework, which is based on a newly introduced classifier called SVM-minus. The presented method is shown to outperform existing techniques on the most challenging and realistic publicly available video face recognition benchmark, both by itself, and in concert with other methods.
Keywords :
face recognition; image classification; support vector machines; video signal processing; 3D head orientation; SVM-minus similarity score; classifier-based similarity scores; face recognition benchmark; image analysis tools; visual similarity; Computational modeling; Face; Face recognition; Optimization; Support vector machines; Training; Vectors; face recognition; pose estimation; similarity score; video; youtube faces;
Conference_Titel :
Computer Vision and Pattern Recognition (CVPR), 2013 IEEE Conference on
Conference_Location :
Portland, OR
DOI :
10.1109/CVPR.2013.452