Journal
IEEE TRANSACTIONS ON IMAGE PROCESSING
Volume 17, Issue 8, Pages 1443-1451Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TIP.2008.925381
Keywords
anisotropic diffusion; disparity estimation; motion estimation; occlusions; optical flow
Funding
- NICHD NIH HHS [1R21HD050655-01] Funding Source: Medline
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Optical flow can be reliably estimated between areas visible in two images, but not in occlusion areas. If optical flow is needed in the whole image domain, one approach is to use additional views of the same scene. If such views are unavailable, an often-used alternative is to extrapolate optical flow in occlusion areas. Since the location of such areas is usually unknown prior to optical flow estimation, this is usually performed in three steps. First, occlusion-ignorant optical flow is estimated, then occlusion areas are identified using the estimated (unreliable) optical flow, and, finally the optical flow is corrected using the computed occlusion areas., This approach, however, does not permit interaction between optical flow and occlusion estimates. In this paper, we permit such interaction by proposing a variational formulation that jointly computes optical flow, implicitly detects occlusions and extrapolates optical flow in occlusion areas. The extrapolation mechanism is based on anisotropic diffusion and uses the underlying image gradient to preserve structure, such as optical flow discontinuities. Our results show significant improvements in the computed optical flow fields over other approaches, both qualitatively and quantitatively.
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