Multi-View Face Detection and Pose Estimation Using a Composite Support Vector Machine across the View Sphere

Authors:
Jeffrey Ng;Shaogang Gong
Affiliations:
-;-
Venue:
RATFG-RTS '99 Proceedings of the International Workshop on Recognition, Analysis, and Tracking of Faces and Gestures in Real-Time Systems
Year:
1999

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Abstract

Support Vector Machines have shown great potential for learning classification functions that can be applied to object recognition. In this work, we extend SVMs to model the 2D appearance of human faces which undergo nonlinear change across the view sphere. The model enables simultaneous multi-view face detection and pose estimation at near-frame rate.