Title :
Multi-view face detection and pose estimation using a composite support vector machine across the view sphere
Author :
Ng, Jeffrey ; Gong, Shaogang
Author_Institution :
Dept. of Comput. Sci., Queen Mary & Westfield Coll., London, UK
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 :
face recognition; image classification; learning (artificial intelligence); object detection; 2D appearance; classification functions; learning; multi-view face detection; object recognition; pose estimation; support vector machine; view sphere; Face detection; Humans; Magnetic heads; Object recognition; Prototypes; Support vector machine classification; Support vector machines; Testing; Training data; Virtual colonoscopy;
Conference_Titel :
Recognition, Analysis, and Tracking of Faces and Gestures in Real-Time Systems, 1999. Proceedings. International Workshop on
Conference_Location :
Corfu
Print_ISBN :
0-7695-0378-0
DOI :
10.1109/RATFG.1999.799218
