An SVD approach to multi-camera-multi-target 3-D motion-shape analysis

S. Y. Kung, J. S. Taur, M. Y. Chiu

Research output: Contribution to journalConference article

3 Scopus citations

Abstract

An SVD approach to the so-called structure-from-motion problem was proposed by Tomasi and Kanade [1992]. The present paper extends the original motion-shape-estimation (MSE) to the multi-camera-multi-target case. The multi-target MSE problem is: given a sequence of 2D video images of multiple moving targets, the problem is to track the 3D motion of the targets and reconstruct their 3D shapes. This is further extended to multi-camera-multi-target MSE, with potential application to the 3D occlusion problem. After collection of feature points (FPs), which are sequentially tracked by a video system, the SVD may be applied to a measurement matrix formed by the FPs. The distribution of singular values would first reveal the information about the number of objects at hand. Then, using an algebraic-based subspace clustering method, the FPs may be mapped onto their corresponding objects. Thereafter, the motion and shape may be estimated from a matrix factorization.

Original languageEnglish (US)
Article number413379
Pages (from-to)573-577
Number of pages5
JournalProceedings - International Conference on Image Processing, ICIP
Volume1
DOIs
StatePublished - Jan 1 1994
EventProceedings of the 1994 1st IEEE International Conference on Image Processing. Part 3 (of 3) - Austin, TX, USA
Duration: Nov 13 1994Nov 16 1994

All Science Journal Classification (ASJC) codes

  • Software
  • Computer Vision and Pattern Recognition
  • Signal Processing

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