Inferring 3D structure with a statistical image-based shape model

Proceedings of the IEEE International Conference on Computer Vision

Volumn 1, Issue , 2003, Pages 641-648

  Grauman, Kristen ^a   Shakhnarovich, Gregory ^a   Darrell, Trevor ^a  

^a MASSACHUSETTS INSTITUTE OF TECHNOLOGY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATIONAL GEOMETRY; COMPUTER SIMULATION; IMAGE RECONSTRUCTION; IMAGE SEGMENTATION; PARAMETER ESTIMATION; PRINCIPAL COMPONENT ANALYSIS; PROBABILITY DENSITY FUNCTION; THREE DIMENSIONAL; VIDEO CAMERAS;

MULTI-VIEW CONTOURS; STATISTICAL IMAGE-BASED SHAPE MODEL; THREE DIMENSIONAL STRUCTURE;

COMPUTER VISION;

EID: 0344982832     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/iccv.2003.1238408     Document Type: Conference Paper

References (17)

1. A. Baumberg and D. Hogg. Learning Flexible Models from Image Sequences. In Proceedings of European Conference on Computer Vision, Stockholm, Sweden, May 1994.
2. A. Baumberg and D. Hogg. An Adaptive Eigenshape Model. In British Machine Vision Conference, pages 87-96, Birmingham, England, Sept 1995.
3. T. Cootes and C. Taylor. A Mixture Model for Representing Shape Variation. In British Machine Vision Conference, pages 110-119, Essex, England, 1997.
4. T. Cootes, C. Taylor, D. Cooper, and J. Graham. Active Shape Models - Their Training and Application. Computer Vision and Image Understanding, 61 (1):38-59, Jan 1995.
5. T. Cootes, G. Wheeler, K. Walker, and C. Taylor. View-Based Active Appearance Models. Image and Vision Computing, 20:657-664, 2002.
6. M. Covell. Eigen-Points: Control-Point Location Using Principal Component Analysis. In Proceedings of the IEEE International Conference on Automatic Face and Gesture Recognition, pages 122-127, Killington, VT, Oct 1996.
7. Egisys Co. Curious Labs. Poser 5: The Ultimate 3D Character Solution. 2002.
8. K. Grauman, G. Shakhnarovich, and T. Darrell. A Bayesian Approach to Image-Based Visual Hull Reconstruction. In Proceedings IEEE Conference on Computer Vision and Pattern Recognition, Madison, WI, June 2003.
9. J. Haslam, C. Taylor, and T. Cootes. A Probabilistic Fitness Measure for Deformable Template Models. In British Machine Vision Conference, pages 33-42, York, England, Sept 1994.
10. M. Jones and T. Poggio. Multidimensional Morphable Models. In Proceedings of the International Conference on Computer Vision, pages, 683-688, Bombay, India, January 1998.
11. A. Laurentini. The Visual Hull Concept for Silhouette-Based Image Understanding. IEEE Transactions on Pattern Analysis and Machine Intelligence, 16(2):150-162, Feb 1994.
12. W. Matusik, C. Buehler, R. Raskar, S. Gortler, and L. McMillan. Image-Based Visual Hulls. In Proceedings ACM Conference on Computer Graphics and Interactive Techniques, pages 369-374, 2000.
13. B. Moghaddam. Principal Manifolds and Probabilistic Sub-spaces for Visual Recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence, 24(6):780-788, June 2002.
14. E-J. Ong and S. Gong. The Dynamics of Linear Combinations. Image and Vision Computing, 20(5-6):397-414, 2002.
15. M. Tipping and C. Bishop. Mixtures of Probabilistic Principal Component Analyzers. Neural Computation, 11(2):443-482, 1999.
16. M. Turk and A. Pentland. Face Recognition Using Eigenfaces. In Proceedings IEEE Conference on Computer Vision and Pattern Recognition, pages 586-590, Maui, HI, June 1991.
17. Y. Wang and L. H. Staib. Boundary Finding with Prior Shape and Smoothness Models. IEEE Transactions on Pattern Analysis and Machine Intelligence, 22(7):738-743, 2000.