“Turning to the masters: motion capturing cartoons”

In this paper, we present a technique we call “cartoon capture and retargeting” which we use to track the motion from traditionally animated cartoons and retarget it onto 3-D models, 2-D drawings, and photographs. By using animation as the source, we can produce new animations that are expressive, exaggerated or non-realistic.Cartoon capture transforms a digitized cartoon into a cartoon motion representation. Using a combination of affine transformation and key-shape interpolation, cartoon capture tracks non-rigid shape changes in cartoon layers. Cartoon retargeting translates this information into different output media. The result is an animation with a new look but with the movement of the original cartoon.

1. ALEXA, M., AND MÜLLER, W. 2000. Representing animations by principal components. 411-418. ISSN 1067-7055.Google Scholar
2. ALEXA, M., COHEN-OR, D., AND LEVIN, D. 2000. As-rigid-as-possible shape interpolation. In Proceedings of SIGGRAPH 2000, ACM Press / ACM SIGGRAPH / Addison Wesley Longman, Computer Graphics Proceedings, Annual Conference Series, 157-164. ISBN 1-58113-208-5. Google Scholar
3. BERGEN, J., ANANDAN, P., HANNA, K., AND HINGORANI, R. 1992. Hierarchical model-based motion estimation. In ECCV, 237-252. Google Scholar
4. BLACK, M., AND JEPSON, A., 1996. Eigentracking: robust matching and tracking of articulated objects using a view-based representation. Google Scholar
5. BLANZ, V., AND VETTER, T. August 1999. A morphable model for the synthesis of 3d faces. Proceedings of SIGGRAPH 99, 187-194. ISBN 0-20148-560-5. Held in Los Angeles, California. Google Scholar
6. BREGLER, C., AND OMOHUNDRO, S. 1994. Surface learning with applications to lipreading. In Advances in Neural Information Processing Systems, Morgan Kaufman, San Francisco, A. Cowan, Tesauro, Ed.Google Scholar
7. CANNY, J. 1986. A computational approach to edge detection. IEEE Trans. Pattern Anal. Mach. Intell. 8, 679-698. Google Scholar
8. GILL, P., MURRAY, W., AND WRIGHT, M. 1981. Practical Optimization. Academic Press, London, UK.Google Scholar
9. GLEICHER, M. 1998. Retargeting motion to new characters. In SIGGRAPH 98 Conference Proceedings, Addison Wesley, M. Cohen, Ed., Annual Conference Series, ACM SIGGRAPH, 33-42. ISBN 0-89791-999-8. Google Scholar
10. HORN, B., AND SCHUNK, G. 1981. Determining optical flow. Artificial Intelligence 17.Google Scholar
11. JOLLIFE, I. T. 1986. Principal Components Analysis. New York: Springer.Google Scholar
12. LANITIS, A., TAYLOR, C., COOTES, T., AND AHMED, T. 1995. Automatic interpretation of human faces and hand gestures using flexible models. In International Workshop on Automatic Face- and Gesture-Recognition.Google Scholar
13. LUCAS, B., AND KANADE, T. 1981. An iterative image registration technique with an application to stereo vision. Proc. 7th Int. Joinnt Conf. on Art. Intell.Google Scholar
14. NGO, T., DANA, J., CUTRELL, D., DONALD, B., LOEB, L., AND ZHU, S. 2000. Accessible animation and customizable graphics via simplicial configuration modeling. In SIGGRAPH 2000 Proceedings. Google Scholar
15. PARKE, F. 1972. Computer generated animation of faces. In ACM National Conferences, 451-457. Google Scholar
16. PIGHIN, F., HECKER, J., LISCHINSKI, D., SZELISKI, R., AND SALESIN, D. H. 1998. Synthesizing realistic facial expressions from photographs. In SIGGRAPH 98 Conference Proceedings, Addison Wesley, M. Cohen, Ed., Annual Conference Series, ACM SIGGRAPH, 75-84. ISBN 0-89791-999-8. Google Scholar
17. POPOVIĆ, Z., AND WITKIN, A. 1999. Physically based motion transformation. In SIGGRAPH 99 Conference Proceedings, ACM SIGGRAPH. Google Scholar
18. SHI, J., AND TOMASI, C. 1994. Good features to track. In CVPR.Google Scholar
19. WHITAKER, H., AND HALAS, J. 1981. Timing for Animation. FOCAL PRESS LTD.Google Scholar
20. YONG NOH, J., AND NEUMANN, U. 2001. Expression cloning. In Proceedings of SIGGRAPH 2001, ACM Press / ACM SIGGRAPH, Computer Graphics Proceedings, Annual Conference Series, 277-288. ISBN 1-58113-292-1. Google Scholar