This paper derives a formal link between temporally weighted frame differences, or disturbance fields, which carry limited information suitable for motion detection, and the optic flow, which carries richer information on local image motion. We use this link to derive a novel, simple, near-recursive optic flow algorithm based on a recursive-filter formulation. Most quantities involved are computed recursively, using only data from the current and previous frame. We can limit expensive OF calculations to pixels where motion magnitude is sufficiently high using image differences which the algorithm computes anyway. Experimental results with well-known synthetic, ground-truthed test sequences and standard performance metrics indicate good quantitative performance. Tests with real sequences suggest similar or better performance than a well-known, similar algorithm due to Lucas and Kanade.
Near-Recursive Optical Flow from Weighted Image Differences
ROBERTO, Vito
2005-01-01
Abstract
This paper derives a formal link between temporally weighted frame differences, or disturbance fields, which carry limited information suitable for motion detection, and the optic flow, which carries richer information on local image motion. We use this link to derive a novel, simple, near-recursive optic flow algorithm based on a recursive-filter formulation. Most quantities involved are computed recursively, using only data from the current and previous frame. We can limit expensive OF calculations to pixels where motion magnitude is sufficiently high using image differences which the algorithm computes anyway. Experimental results with well-known synthetic, ground-truthed test sequences and standard performance metrics indicate good quantitative performance. Tests with real sequences suggest similar or better performance than a well-known, similar algorithm due to Lucas and Kanade.File | Dimensione | Formato | |
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