Energy flow: image correspondence approximation for motion analysis

Liangliang Wang; Ruifeng Li; Yajun Fang

doi:10.1117/1.OE.55.4.043109

29 April 2016 Energy flow: image correspondence approximation for motion analysis

Liangliang Wang, Ruifeng Li, Yajun Fang

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Optical Engineering, Vol. 55, Issue 4, 043109 (April 2016). https://doi.org/10.1117/1.OE.55.4.043109

Abstract

We propose a correspondence approximation approach between temporally adjacent frames for motion analysis. First, energy map is established to represent image spatial features on multiple scales using Gaussian convolution. On this basis, energy flow at each layer is estimated using Gauss–Seidel iteration according to the energy invariance constraint. More specifically, at the core of energy invariance constraint is “energy conservation law” assuming that the spatial energy distribution of an image does not change significantly with time. Finally, energy flow field at different layers is reconstructed by considering different smoothness degrees. Due to the multiresolution origin and energy-based implementation, our algorithm is able to quickly address correspondence searching issues in spite of background noise or illumination variation. We apply our correspondence approximation method to motion analysis, and experimental results demonstrate its applicability.

CC BY: © The Authors. Published by SPIE under a Creative Commons Attribution 4.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.

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Liangliang Wang, Ruifeng Li, and Yajun Fang "Energy flow: image correspondence approximation for motion analysis," Optical Engineering 55(4), 043109 (29 April 2016). https://doi.org/10.1117/1.OE.55.4.043109

Published: 29 April 2016

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