Application of SVD networks to multi-object motion-shape analysis

Sun-Yuan Kung, J. S. Taur, M. Y. Chiu

Research output: Contribution to conferencePaper

2 Scopus citations

Abstract

The paper discusses the evolution of the single object motion shape estimation (MSE) problem. Given a sequence of 2-D video images of multiple moving objects, the problem is to track the 3-D motion of the objects and reconstruct their 3-D shapes. After selection of initial feature points (FPs), the SVD may be applied to a measurement matrix formed by the FPs sequentially tracked by a video system. The distribution of singular values first reveal the information about the number of objects at hand. Then, using an algebraic-based subspace clustering method, the FPs are mapped onto their corresponding objects. Thereafter, the motion and shape are be estimated from a matrix factorization.

Original languageEnglish (US)
Pages413-422
Number of pages10
StatePublished - Dec 1 1994
EventProceedings of the 4th IEEE Workshop on Neural Networks for Signal Processing (NNSP'94) - Ermioni, GREECE
Duration: Sep 6 1994Sep 8 1994

Other

OtherProceedings of the 4th IEEE Workshop on Neural Networks for Signal Processing (NNSP'94)
CityErmioni, GREECE
Period9/6/949/8/94

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Software
  • Electrical and Electronic Engineering

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  • Cite this

    Kung, S-Y., Taur, J. S., & Chiu, M. Y. (1994). Application of SVD networks to multi-object motion-shape analysis. 413-422. Paper presented at Proceedings of the 4th IEEE Workshop on Neural Networks for Signal Processing (NNSP'94), Ermioni, GREECE, .