1 September 1995 Curvature and aggregate velocity for optical flow
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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.
© (1995) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Gary A. Hewer, Charles Kenney, Wei Kuo, Lawrence A. Peterson, "Curvature and aggregate velocity for optical flow", Proc. SPIE 2567, Investigative and Trial Image Processing, (1 September 1995); doi: 10.1117/12.218465; https://doi.org/10.1117/12.218465
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