Multi-view face detection and pose estimation using a composite support vector machine across the view sphere
- 20 January 2003
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
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.Keywords
This publication has 6 references indexed in Scilit:
- An investigation into face pose distributionsPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- Training support vector machines: an application to face detectionPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- Exploiting Context in Gesture RecognitionPublished by Springer Nature ,1999
- Fusion of Perceptual Cues using Covariance EstimationPublished by British Machine Vision Association and Society for Pattern Recognition ,1999
- Learning to Associate Faces across Views in Vector Space of Similarities to PrototypesPublished by British Machine Vision Association and Society for Pattern Recognition ,1998
- The Nature of Statistical Learning TheoryPublished by Springer Nature ,1995