Learning bilinear models for two-factor problems in vision

In many vision problems, we want to infer two (or more) hidden factors which interact to produce our observations. We may want to disentangle illuminant and object colors in color constancy; rendering conditions from surface shape in shape-from-shading; face identity and head pose in face recognition; or font and letter class in character recognition. We refer to these two factors generically as ¨style¨and ¨content¨. This paper received Outstanding Paper prize, CVPR ´97. Proc. IEEE Computer Vision and Pattern Recognition (CVPR ´97), Puerto Rico This work may not be copied or reproduced in whole or in part for any commercial purpose. Permission to copy in whole or in part without payment of fee is granted for nonprofit educational and research purposes provided that all such whole or partial copies include the following: a notice that such copying is by permission of Mitsubishi Electric Research Laboratories, Inc.; an acknowledgment of the authors and individual contributions to...

• Type: Conference
• Year: 1997
• Where: CVPR
• Authors: William T. Freeman, Joshua B. Tenenbaum
• Keywords: Computer Vision, CVPR 1997, Electric Research Laboratories, Mitsubishi Electric Research, Rico This Work