Energy flow: image correspondence approximation for motion analysis
Name
Wang-2016-Energy flow_ image c.pdf
Size
3.48 MB
Format
Adobe PDF
Checksum (MD5)
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Author(s)
Wang, Liangliang
Li, Ruifeng
Fang, Yajun
Date Issued
April 2016
Journal
Optical Engineering
Publisher
SPIE
Citation
Wang, Liangliang, Ruifeng Li, and Yajun Fang. "Energy flow: image correspondence approximation for motion analysis." Optical Engineering 55:4 (April 2016), 043109-1.
Version
Final published version
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.
MIT Department
Massachusetts Institute of Technology. Microsystems Technology Laboratories
Terms of Use
Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1117/1.oe.55.4.043109
