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
Artificial intelligenceComputer scienceSupport vector machineClassifier (UML)Pattern recognition (psychology)Facial recognition systemSpurious relationshipSimilarity (geometry)ConfusionFace (sociological concept)Computer visionMachine learningImage (mathematics)
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Publication Info
- Year
- 2013
- Type
- article
- Pages
- 3523-3530
- Citations
- 66
- Access
- Closed
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Cite This
Lior Wolf,
Noga Levy
(2013).
The SVM-Minus Similarity Score for Video Face Recognition.
, 3523-3530.
https://doi.org/10.1109/cvpr.2013.452
Identifiers
- DOI
- 10.1109/cvpr.2013.452