Paper
30 May 2000 Motion estimation using adaptive matching and multiscale methods
Stephanus Suryadarma, Teddy Surya Gunawan, Chong Man Nang
Author Affiliations +
Proceedings Volume 4067, Visual Communications and Image Processing 2000; (2000) https://doi.org/10.1117/12.386553
Event: Visual Communications and Image Processing 2000, 2000, Perth, Australia
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.
© (2000) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Stephanus Suryadarma, Teddy Surya Gunawan, and Chong Man Nang "Motion estimation using adaptive matching and multiscale methods", Proc. SPIE 4067, Visual Communications and Image Processing 2000, (30 May 2000); https://doi.org/10.1117/12.386553
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Cited by 7 scholarly publications.
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KEYWORDS
Motion estimation

Motion models

Video

Motion measurement

Filtering (signal processing)

Magnetorheological finishing

Image processing

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