Stereo vision-based variational optical flow estimation

Optical flow computation is one of the most important tasks in computer vision. The article deals with a modification of the variational method of the optical flow computation, according to its application in stereo vision. Such approaches are traditionally based on a brightness constancy assumption...

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Bibliographic Details
Published in:E3S web of conferences 2020-01, Vol.224, p.1027
Main Authors: Belyakov, P. V., Nikiforov, M. B., Muratov, E. R., Melnik, O. V.
Format: Article
Language:English
Subjects:
Cameras
Computation
Computer vision
Differential equations
Fields (mathematics)
Image processing
Optical flow (image analysis)
Partial differential equations
Pedestrians
Pixels
Smoothness
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Summary:Optical flow computation is one of the most important tasks in computer vision. The article deals with a modification of the variational method of the optical flow computation, according to its application in stereo vision. Such approaches are traditionally based on a brightness constancy assumption and a gradient constancy assumption during pixels motion. Smoothness assumption also restricts motion discontinuities, i.e. the smoothness of the vector field of pixel velocity is assumed. It is proposed to extend the functional of the optical flow computation in a similar way by adding a priori known stereo cameras extrinsic parameters and minimize such jointed model of optical flow computation. The article presents a partial differential equations framework in image processing and numerical scheme for its implementation. Performed experimental evaluation demonstrates that the proposed method gives smaller errors than traditional methods of optical flow computation.
ISSN:2267-1242
2555-0403
2267-1242
DOI:10.1051/e3sconf/202022401027