Occlusion-Aware Optical Flow Estimation

• Published in: IEEE transactions on image processing Vol. 17; no. 8; pp. 1443 - 1451
• Main Authors: Ince, S., Konrad, J.
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.08.2008; Institute of Electrical and Electronics Engineers; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Anisotropic diffusion; Anisotropic magnetoresistance; Applied sciences; Computation; Detection, estimation, filtering, equalization, prediction; Diffusion; Discontinuity; disparity estimation; Estimates; Exact sciences and technology; Extrapolation; Geometrical optics; Image Enhancement - methods; Image Interpretation, Computer-Assisted - methods; Image motion analysis; Image processing; Imaging, Three-Dimensional - methods; Information, signal and communications theory; Layout; Miscellaneous; Motion estimation; Occlusion; occlusions; Optical computing; Optical detectors; optical flow; Preserves; Rendering (computer graphics); Reproducibility of Results; Rheology - methods; Sensitivity and Specificity; Signal and communications theory; Signal processing; Signal, noise; Telecommunications and information theory; Video Recording - methods; Video sequences; Motion estimation; Image processing; Signal estimation; Optical field; Flow field; Anisotropic diffusion; occlusions; Signal processing; Anisotropic scattering; Disparity; Localization; disparity estimation; Optical flow
• ISSN: 1057-7149; 1941-0042
• DOI: 10.1109/TIP.2008.925381

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.