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Proceedings Paper

Motion estimation using adaptive matching and multiscale methods
Author(s): Stephanus Suryadarma; Teddy Surya Gunawan; Chong Man Nang
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Paper Abstract

Past approaches on motion estimation use iterative algorithm to produce dense motion fields, which is modeled by the energy functions. The optimization strategy such as simulated annealing or iterated conditional mode reorganize the motion fields slowly. This paper introduces adaptive block matching and multiscale smoothing as an initial motion fields for bayesian based motion estimation. The adaptive block matching is a local intensity matching procedure, which gives a unique matching results. The results are smoothed by multiscale smoothing algorithm. This algorithm is based on kalman filter, but the time domain of this filter becomes the scale domain. The result shows that this strategy can give a more global motion fields than the result of single resolution bayesian motion estimation method. This multiscale smoothing algorithm have numerous possibility to enhance the speed as well as strategy to produce better motion fields.

Paper Details

Date Published: 30 May 2000
PDF: 12 pages
Proc. SPIE 4067, Visual Communications and Image Processing 2000, (30 May 2000); doi: 10.1117/12.386553
Show Author Affiliations
Stephanus Suryadarma, Nanyang Technological Univ. (Singapore)
Teddy Surya Gunawan, Nanyang Technological Univ. (Singapore)
Chong Man Nang, Nanyang Technological Univ. (Singapore)

Published in SPIE Proceedings Vol. 4067:
Visual Communications and Image Processing 2000
King N. Ngan; Thomas Sikora; Ming-Ting Sun, Editor(s)

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