Towards Ultimate Motion Estimation: Combining Highest Accuracy with Real-Time Performance
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1 - Volume 01
Particle Video: Long-Range Motion Estimation Using Point Trajectories
International Journal of Computer Vision
Robust motion estimation under varying illumination
Image and Vision Computing
Illumination-robust variational optical flow with photometric invariants
Proceedings of the 29th DAGM conference on Pattern recognition
A duality based approach for realtime TV-L1 optical flow
Proceedings of the 29th DAGM conference on Pattern recognition
A duality based algorithm for TV-L¹-optical-flow image registration
MICCAI'07 Proceedings of the 10th international conference on Medical image computing and computer-assisted intervention
Illumination-robust variational optical flow using cross-correlation
Computer Vision and Image Understanding
International Journal of Computer Vision
Illumination-robust dense optical flow using census signatures
DAGM'11 Proceedings of the 33rd international conference on Pattern recognition
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The brightness constancy assumption is the base of estimating the flow fields in most differential optical flow approaches. However, the brightness constancy constraint easily violates with any variation in the lighting conditions in the scene. Thus, this work proposes a robust data term against illumination changes based on a rich descriptor. This descriptor extracts the textures features for each image in the two consecutive images using local edge responses. In addition, a weighted non-local term depending on the intensity similarity, the spatial distance and the occlusion state of pixels is integrated within the adapted duality total variational optical flow algorithm in order to obtain accurate flow fields. The proposed model yields state-of-the-art results on the the KITTI optical flow database and benchmark.