Deriving intrinsic images from image sequences

Proceedings of the IEEE International Conference on Computer Vision

Volumn 2, Issue , 2001, Pages 68-75

  Weiss, Y ^a  

^a UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; COMPUTER VISION; MAXIMUM LIKELIHOOD ESTIMATION; PERFORMANCE; REFLECTION; THEOREM PROVING;

ILLUMINATION IMAGE; INTRINSIC IMAGES; REFLECTANCE IMAGE;

IMAGE ANALYSIS;

EID: 0034844255     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (12)

1. Recovering intrinsic scene characteristics from images
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3. Bayesian model of surface perception
4. Recovering shading from color images
5. From few to many: Generative models for recognition under variable pose and illumination
6. Photometric stereo under a light source with arbitrary motions
7. Lightness and retinex theory
8. Emergence of simple-cell receptive field properties by learning a sparse code for natural images
9. Construction and refinement of panoramic mosaics with global and local alignment
10. Statistical models for images: Compression restoration and synthesis
11. Layer extraction from multiple images containing reflections and transparency
12. Determining generative models of objects under varying illumination: Shape and albedo from multiple images using SVD and integrability