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Article Dans Une Revue Computer Vision and Image Understanding Année : 2016

Illumination invariant optical flow using neighborhood descriptors

Résumé

Total variational (TV) methods using l1-norm are efficient approaches for optical flow determination. This contribution presents a multi-resolution TV-l1 approach using a data-term based on neighborhood descriptors and a weighted non-local regularizer. The proposed algorithm is robust to illumination changes. The benchmarking of the proposed algorithm is done with three reference databases (Middlebury, KITTI and MPI Sintel). On these databases, the proposed approach exhibits an optimal compromise between robustness, accuracy and computation speed. Numerous tests performed both on complicated data of the reference databases and on challenging endoscopic images acquired under three different modalities demonstrate the robustness and accuracy of the method against the presence of large or small displacements, weak texture information, varying illumination conditions and modality changes.
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Dates et versions

hal-01244632 , version 1 (16-12-2015)

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Sharib Ali, Christian Daul, Ernest Galbrun, Walter Blondel. Illumination invariant optical flow using neighborhood descriptors. Computer Vision and Image Understanding, 2016, 145, pp.95-110. ⟨10.1016/j.cviu.2015.12.003⟩. ⟨hal-01244632⟩
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