Shape Recipes: Scene Representations that Refer to the Image

NIPS 2002: Proceedings of the 15th International Conference on Neural Information Processing Systems

Volumn , Issue , 2002, Pages 1335-1342

  Freeman, William T ^a   Torralba, Antonio ^a  

^a MASSACHUSETTS INSTITUTE OF TECHNOLOGY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

COMPLEX SCENES; DIMENSIONAL REPRESENTATION; HIGH-DIMENSIONAL; HIGHER-DIMENSIONAL; LOW-DIMENSIONAL REPRESENTATION; LOW-LEVEL VISION; REAL-WORLD; REGRESSION COEFFICIENT; SCENE REPRESENTATION; SHAPE-FROM-IMAGE;

EID: 0042003417     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (19)

1. E. H. Adelson. Lightness perception and lightness illusions. In M. Gazzaniga, editor, The New Cognitive Neurosciences, pages 339-351. MIT Press, 2000.
2. C. M. Bishop. Neural networks for pattern recognition. Oxford, 1995.
3. A. Gilchrist et al. An anchoring theory of lightness. Psychological Review, 106(4):795-834, 1999.
4. W. T. Freeman. The generic viewpoint assumption in a framework for visual perception. Nature, 368(6471):542-545, April 7 1994.
5. B. K. P. Horn and M. J. Brooks, editors. Shape from shading. The MIT Press, Cambridge, MA, 1989.
6. T. Leung and J. Malik. Representing and recognizing the visual appearance of materials using three-dimensional textons. Intl. J. Comp. Vis., 43(1):29-44, 2001.
7. A. P. Pentland. Linear shape from shading. Intl. J. Comp. Vis., 1(4):153-162, 1990.
8. M. Pollefeys, R. Koch, and L. V. Gool. A simple and efficient rectification method for general motion. In Intl. Conf. on Computer Vision (ICCV), pages 496-501, 1999.
9. R. A. Rensink. The dynamic representation of scenes. Vis. Cognition, 7:17-42, 2000.
10. S. Sclaroff and A. Pentland. Generalized implicit functions for computer graphics. In Proc. SIGGRAPH 91, volume 25, pages 247-250, 1991. In Computer Graphics, Annual Conference Series.
11. J. Shi and J. Malik. Normalized cuts and image segmentation. IEEE Pattern Analysis and Machine Intelligence, 22(8):888-905, 2000.
12. E. P. Simoncelli. Statistical models for images: Compression, restoration and synthesis. In 31st Asilomar Conf. on Sig., Sys. and Computers, Pacific Grove, CA, 1997.
13. E. P. Simoncelli and W. T. Freeman. The steerable pyramid: a flexible architecture for multi-scale derivative computation. In 2nd Annual Intl. Conf. on Image Processing, Washington, DC, 1995. IEEE.
14. R. Szeliski. Bayesian modeling of uncertainty in low-level vision. Intl. J. Comp. Vis., 5(3):271-301, 1990.
15. M. F. Tappen, W. T. Freeman, and E. H. Adelson. Recovering intrinsic images from a single image. In Adv. in Neural Info. Proc. Systems, volume 15. MIT Press, 2003.
16. A. Torralba and W. T. Freeman. Properties and applications of shape recipes. Technical Report AIM-2002-019, MIT AI lab, 2002.
17. Y. Weiss. Bayesian motion estimation and segmentation. PhD thesis, M.I.T., 1998.
18. Z. Zhang. Determining the epipolar geometry and its uncertainty: A review. Technical Report 2927, Sophia-Antipolis Cedex, France, 1996. see http://wwwsop.inria.fr/robotvis/demo/f-http/html/.
19. C. L. Zitnick and T. Kanade. A cooperative algorithm for stereo matching and occlusion detection. IEEE Pattern Analysis and Machine Intelligence, 22(7), July 2000.