Functional categorization of objects using real-time markerless motion capture

Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition

Volumn , Issue , 2011, Pages 1969-1976

  Gall, Juergen ^a   Fossati, Andrea ^a   Van Gool, Luc ^a,b  

^a ETH ZURICH   (Switzerland)

^b UNIVERSITY OF LEUVEN   (Belgium)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER SCIENCE; COMPUTERS; ELECTRICAL ENGINEERING; PATTERN RECOGNITION; SOFTWARE ENGINEERING;

APPEARANCE-BASED METHODS; HUMAN DEMONSTRATIONS; MARKERLESS MOTION CAPTURE; MOTION CAPTURE DATA; OBJECT CATEGORIZATION; OBJECT MANIPULATION; VIDEO SEGMENTS; VIDEO SEQUENCES;

COMPUTER VISION;

EID: 80052891496     PISSN: 10636919     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2011.5995582     Document Type: Conference Paper

References (35)

1. E. Aksoy, A. Abramov, F. Wörgötter, and B. Dellen. Categorizing object-action relations from semantic scene graphs. In Proc. Int. Conf. on Rob. and Automation, 2010.
2. A. Balan and M. Black. The naked truth: Estimating body shape under clothing. In Proc. ECCV, pages 15-29, 2008.
3. I. Baran and J. Popović. Automatic rigging and animation of 3d characters. ACM Trans. Graph., 26(3):72, 2007.
4. A. Booth. The facilitative effect of agent-produced motions on categorization in infancy. Infant Behavior and Development, 23(2):153-174, 2000.
5. C. Bregler, J. Malik, and K. Pullen. Twist based acquisition and tracking of animal and human kinematics. IJCV, 56(3):179-194, 2004.
6. J. Deutscher and I. Reid. Articulated body motion capture by stochastic search. IJCV, 61(2):185-205, 2005.
7. M. Everingham, L. V. Gool, C. Williams, J. Winn, and A. Zisserman. The pascal visual object classes (voc) challenge. IJCV, 88:303-338, 2010.
8. R. Filipovych and E. Ribeiro. Recognizing primitive interactions by exploring actor-object states. Proc. CVPR, 2008.
9. A. Fossati, M. Dimitrijevic, V. Lepetit, and P. Fua. From canonical poses to 3-d motion capture using a single camera. PAMI, 32(7):1165-1181, 2010.
10. J. Gall and V. Lempitsky. Class-specific hough forests for object detection. In Proc. CVPR, 2009.
11. J. Gall, B. Rosenhahn, T. Brox, and H.-P. Seidel. Optimization and filtering for human motion capture - a multi-layer framework. IJCV, 87(1):75-92, 2010.
12. V. Ganapathi, C. Plagemann, S. Thrun, and D. Koller. Real time motion capture using a single time-of-flight camera. In Proc. CVPR, 2010.
13. J. Gibson. The Ecological Approach to Visual Perception. Boston: Houghton Mifflin Company, 1979.
14. A. Gupta and L. Davis. Objects in action: An approach for combining action understanding and object perception. In Proc. CVPR, 2007.
15. N. Hasler, C. Stoll, M. Sunkel, B. Rosenhahn, and H.-P. Seidel. A statistical model of human pose and body shape. Computer Graphics Forum, 2(28), 2009.
16. H. Kjellström, J. Romero, and D. Kragic. Visual objectaction recognition: Inferring object affordances from human demonstration. CVIU, 2010.
17. S. Knoop, S. Vacek, and R. Dillmann. Sensor fusion for 3d human body tracking with an articulated 3d body model. In Proc. Int. Conf. on Rob. and Automation, 2006.
18. V. Levenshtein. Binary Codes Capable of Correcting Deletions, Insertions and Reversals. Soviet Physics Doklady, 10, 1966.
19. T. Moeslund, A. Hilton, and V. Krüger. A survey of advances in vision-based human motion capture and analysis. CVIU, 104(2):90-126, 2006.
20. D. Moore, I. Essa, and M. Hayes. Exploiting human actions and object context for recognition tasks. In Proc. ICCV, 1999.
21. B. Ommer, T. Mader, and J. Buhmann. Seeing the Objects Behind the Dots: Recognition in Videos from a Moving Camera. IJCV, 83:57-71, 2009.
22. P. Peursum, G. West, and S. Venkatesh. Combining image regions and human activity for indirect object recognition in indoor wide-angle views. In Proc. ICCV, 2005.
23. C. Plagemann, V. Ganapathi, D. Koller, and S. Thrun. Realtime identification and localization of body parts from depth images. In Proc. Int. Conf. on Rob. and Automation, 2010.
24. R. Poppe. A survey on vision-based human action recognition. Image and Vision Computing, 28:976-990, 2010.
25. L. Rabiner and B. Juang. Fundamentals of Speech Recognition. Prentice-Hall, Englewood Cliffs, NJ, 1993.
26. D. Ramanan, D. A. Forsyth, and A. Zisserman. Strike a pose: Tracking people by finding stylized poses. In Proc. CVPR, pages 271-278, 2005.
27. E. Rivlin, S. J. Dickinson, and A. Rosenfeld. Recognition by functional parts. CVIU, 62:164-176, 1995.
28. L. Sigal, A. Balan, and M. Black. Humaneva: Synchronized video and motion capture dataset and baseline algorithm for evaluation of articulated human motion. IJCV, 87:4-27, 2010.
29. L. Stark and K. Bowyer. Achieving generalized object recognition through reasoning about association of function to structure. PA M I, 13:1097-1104, 1991.
30. M. W. Turek, A. Hoogs, and R. Collins. Unsupervised learning of functional categories in video scenes. In Proc. ECCV, 2010.
31. T. Tuytelaars, C. H. Lampert, M. B. Blaschko, and W. Buntine. Unsupervised object discovery: A comparison. IJCV, 88:284-302, 2010.
32. D. Weinland, E. Boyer, and R. Ronfard. Action recognition from arbitrary views using 3d exemplars. In Proc. ICCV, 2007.
33. J. Wu, A. Osuntogun, T. Choudhury, M. Philipose, and J. Rehg. A scalable approach to activity recognition based on object use. In Proc. ICCV, 2007.
34. F. Zhou, F. De la Torre, and J. K. Hodgins. Aligned cluster analysis for temporal segmentation of human motion. In IEEE Conf. on Aut. Face and Gestures Recognition, 2008.
35. Y. Zhu and B. Dariush. Constrained optimization for human pose estimation from depth sequences. In Proc. ACCV, 2007.