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Proceedings Paper

Curvature and aggregate velocity for optical flow
Author(s): Gary A. Hewer; Charles Kenney; Wei Kuo; Lawrence A. Peterson
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Paper Abstract

This paper presents results on an approach to optical flow estimation and image segmentation based on treating the flow of image level sets rather than individual points. This allows the accurate estimation of object velocity even from low quality video sequences and has the advantage of simplifying the analysis of classical ill-condition problems for optical flow estimation such as the aperutre effect. This procedure has been tailored to motion estimation for small to intermediate sized objects and can be applied to the problem of estimating human locomotion from image sequences. Under reasonable assumptions it is shown analytically that the condition number of the from image sequences. Under reasonable assumptions it is shown analytically that the condition number of the aggregate velocity equations from optical flow is related in a natural way to the curvature of the image level set at the point of velocity estimation. The provides a link with affine invariant image processing and opens the door to curvature based chaining methods for estimating the flow velocity of moving targets. Numberical examples are presented illustrating the advantages of this approach over competing methods.

Paper Details

Date Published: 1 September 1995
PDF: 8 pages
Proc. SPIE 2567, Investigative and Trial Image Processing, (1 September 1995); doi: 10.1117/12.218465
Show Author Affiliations
Gary A. Hewer, Naval Air Warfare Ctr. (United States)
Charles Kenney, Naval Air Warfare Ctr. (United States)
Wei Kuo, Naval Air Warfare Ctr. (United States)
Lawrence A. Peterson, Naval Air Warfare Ctr. (United States)


Published in SPIE Proceedings Vol. 2567:
Investigative and Trial Image Processing
Leonid I. Rudin; Simon K. Bramble, Editor(s)

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