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MESD: Exploring Optical Flow Assessment on Edge of Motion Objects with Motion Edge Structure Difference

arXiv 2104.05916 ↗First posted 13 Apr 2021cs.CVcited by 0

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Abstract (arXiv)

The optical flow estimation has been assessed in various applications. In this paper, we propose a novel method named motion edge structure difference(MESD) to assess estimation errors of optical flow fields on edge of motion objects. We implement comparison experiments for MESD by evaluating five representative optical flow algorithms on four popular benchmarks: MPI Sintel, Middlebury, KITTI 2012 and KITTI 2015. Our experimental results demonstrate that MESD can reasonably and discriminatively assess estimation errors of optical flow fields on motion edge. The results indicate that MESD could be a supplementary metric to existing general assessment metrics for evaluating optical flow algorithms in related computer vision applications.

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References · 8

  1. 2020RAFT: Recurrent All-Pairs Field Transforms for Optical Flowcited by 2,385
  2. 2015FlowNet: Learning Optical Flow with Convolutional Networkscited by 1,054
  3. 2017PWC-Net: CNNs for Optical Flow Using Pyramid, Warping, and Cost Volumecited by 966
  4. 2016FlowNet 2.0: Evolution of Optical Flow Estimation with Deep Networkscited by 780
  5. 2017Optical Flow Guided Feature: A Fast and Robust Motion Representation for Video Action Recognitioncited by 82
  6. 2015EpicFlow: Edge-Preserving Interpolation of Correspondences for Optical Flowcited by 80
  7. 2017On the Integration of Optical Flow and Action Recognitioncited by 42
  8. 2019Learning Multi-Human Optical Flowcited by 26

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