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N.: The svm-minus similarity score for video face recognition (2013)
| Content Provider | CiteSeerX |
|---|---|
| Author | Wolf, Lior Levy, Noga |
| Abstract | Face recognition in unconstrained videos requires spe-cialized tools beyond those developed for still images: the fact that the confounding factors change state during the video sequence presents a unique challenge, but also an op-portunity to eliminate spurious similarities. Luckily, a ma-jor 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 dis-count 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 exist-ing techniques on the most challenging and realistic pub-licly available video face recognition benchmark, both by itself, and in concert with other methods. 1. |
| File Format | |
| Publisher Date | 2013-01-01 |
| Access Restriction | Open |
| Subject Keyword | Video Face Recognition Svm-minus Similarity Score Visual Similarity Video Sequence Confounding Factor Image Analysis Tool Spurious Similarity Effective Way Head Orientation Exist-ing Technique Classifier-based Similarity Score Face Recognition Presented Method Spe-cialized Tool Accurate Estimation Unique Challenge Ma-jor Source Dis-count Pose Induced Similarity |
| Content Type | Text |
