Morphable Models for the Analysis and Synthesis of Complex Motion Patterns

  • Authors:

  • Martin A. Giese;Tomaso Poggio

  • Affiliations:

  • Center for Biological and Computational Learning, Artificial Intelligence Laboratory, M.I.T., Cambridge, MA, USA. giese@mit.edu;Center for Biological and Computational Learning, Artificial Intelligence Laboratory, M.I.T., Cambridge, MA, USA. tp@ai.mit.edu

  • Venue:
  • International Journal of Computer Vision - special issue on learning and vision at the center for biological and computational learning, Massachusetts Institute of Technology
  • Year:
  • 2000

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Abstract

The linear combination of prototypical views provides a powerful approach for the recognition and the synthesis of images of stationary three-dimensional objects. In this article, we present initial results that demonstrate that similar ideas can be developed for the recognition and synthesis of complex motion patterns. We present a technique that permits to represent complex motion or action patterns by linear combinations of a small number of prototypical image sequences. We demonstrate the applicability of this new approach for the synthesis and analysis of biological motion using simulated and real video data from different locomotion patterns. Our results show that complex motion patterns are embedded in pattern spaces with a defined topological structure, which can be uncovered with our methods. The underlying pattern space seems to have locally, but not globally, the properties of a linear vector space. We show how the knowledge about the topology of the pattern space can be exploited during pattern recognition. Our method may provide a new interesting approach for the analysis and synthesis of video sequences and complex movements.