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Continual Occlusion and Optical Flow Estimation

  • Michal NeoralEmail author
  • Jan Šochman
  • Jiří Matas
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11364)

Abstract

Two optical flow estimation problems are addressed: (i) occlusion estimation and handling, and (ii) estimation from image sequences longer than two frames. The proposed ContinualFlow method estimates occlusions before flow, avoiding the use of flow corrupted by occlusions for their estimation. We show that providing occlusion masks as an additional input to flow estimation improves the standard performance metric by more than 25% on both KITTI and Sintel. As a second contribution, a novel method for incorporating information from past frames into flow estimation is introduced. The previous frame flow serves as an input to occlusion estimation and as a prior in occluded regions, i.e. those without visual correspondences. By continually using the previous frame flow, ContinualFlow performance improves further by 18% on KITTI and 7% on Sintel, achieving top performance on KITTI and Sintel.

Notes

Acknowledgements

The research was supported by Toyota Motor Europe, CTU student grant SGS17/185/OHK3/3T/13 and the OP VVV MEYS project CZ.02.1.01/0.0/0.0/16_019/0000765 Research Center for Informatics.

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Center for Machine Perception, Faculty of Electrical EngineeringCzech Technical University in PraguePragueCzech Republic

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