Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 7-Day Trial for You or Your Team.

Learn More →

Determining Optical Flow

Determining Optical Flow Optical flow cannot be computed locally, since only one independent measurement is available from the image sequence at a point, while the flow velocity has two components. A second constraint is needed. A method for finding the optical flow pattern is presented which assumes that the apparent velocity of the brightness pattern varies smoothly almost everywhere in the image. An iterative implementation is shown which successfully computes the optical flow for a number of synthetic image sequences. The algorithm is robust in that it can handle image sequences that are quantized rather coarsely in space and time. It is also insensitive to quantization of brightness levels and additive noise. Examples are included where the assumption of smoothness is violated at singular points or along lines in the image. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Proceedings of SPIE SPIE

Determining Optical Flow

Download PDF
13 pages

Loading next page...
 
/lp/spie/determining-optical-flow-qPwaJcZHEM

References

References for this paper are not available at this time. We will be adding them shortly, thank you for your patience.

Publisher
SPIE
Copyright
COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.
ISSN
0277-786X
eISSN
1996-756X
DOI
10.1117/12.965761
Publisher site
See Article on Publisher Site

Abstract

Optical flow cannot be computed locally, since only one independent measurement is available from the image sequence at a point, while the flow velocity has two components. A second constraint is needed. A method for finding the optical flow pattern is presented which assumes that the apparent velocity of the brightness pattern varies smoothly almost everywhere in the image. An iterative implementation is shown which successfully computes the optical flow for a number of synthetic image sequences. The algorithm is robust in that it can handle image sequences that are quantized rather coarsely in space and time. It is also insensitive to quantization of brightness levels and additive noise. Examples are included where the assumption of smoothness is violated at singular points or along lines in the image.

Journal

Proceedings of SPIE – SPIE

Published: Nov 12, 1981

There are no references for this article.