MOTION MODELING AND PREDICTION.

Juyang Weng, Narendra Ahuja, Thomas S Huang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

A model-based approach is presented that assumes locally constant angular momentum (LCAM). The model constrains the motion, over a local frame subsequence, to be a superposition of precession and translation. The trajectory of the rotation center is approximated by a vector polynomial. The nature and parameters of short-term motion can be estimated continuously with the goal of understanding motion through the image sequence. Noise smoothing is achieved by overdetermination and a least-squares criterion. Based on the assumption that the motion is smooth, object positions and motion in the near future can be predicted, and short missing subsequences can be recovered.

Original languageEnglish (US)
Title of host publicationProceedings - International Conference on Pattern Recognition
PublisherIEEE
Pages1107-1109
Number of pages3
ISBN (Print)0818607424
StatePublished - Dec 1 1986

Publication series

NameProceedings - International Conference on Pattern Recognition

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition

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  • Cite this

    Weng, J., Ahuja, N., & Huang, T. S. (1986). MOTION MODELING AND PREDICTION. In Proceedings - International Conference on Pattern Recognition (pp. 1107-1109). (Proceedings - International Conference on Pattern Recognition). IEEE.