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Asian Conference on Computer Vision

ACCV 2018: Computer Vision – ACCV 2018 pp 597–612Cite as

Pooling-Based Feature Extraction and Coarse-to-fine Patch Matching for Optical Flow Estimation

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Part of the Lecture Notes in Computer Science book series (LNIP,volume 11364)

Abstract

This paper presents a pooling-based hierarchical model to extract a dense matching set for optical flow estimation. The proposed model down-samples basic image features (gradient and colour) with min and max pooling, to maintain distinctive visual features from the original resolution to the highly down-sampled layers. Subsequently, patch descriptors are extracted from the pooling results for coarse-to-fine patch matching. In the matching process, the local optimum correspondence of patches is found with a four-step search, and then refined by a velocity propagation algorithm. This paper also presents a method to detect matching outliers by checking the consistency of motion-based and colour-based segmentation. We evaluate the proposed method on two benchmarks, MPI-Sintel and Kitti-2015, using two criteria: the matching accuracy and the accuracy of the resulting optical flow estimation. The results indicate that the proposed method is more efficient, produces more matches than the existing algorithms, and improves significantly the accuracy of optical flow estimation.

Keywords

  • Optical flow estimation
  • Coarse-to-fine patch matching
  • Pooling-based feature extraction

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Notes

  1. 1.

    sintel.is.tue.mpg.de.

  2. 2.

    www.cvlibs.net/datasets/kitti.

  3. 3.

    Dthoth.inrialpes.fr/src/deepflow/.

  4. 4.

    github.com/YinlinHu/CPM.

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Author information

Authors and Affiliations

  1. School of Electrical, Computer and Telecommunications Engineering, University of Wollongong, Wollongong, NSW, 2522, Australia

    Xiaolin Tang, Son Lam Phung, Abdesselam Bouzerdoum & Van Ha Tang

  2. Division of Information and Computing Technology, College of Science and Engineering, Hamad Bin Khalifa University, PO Box 5825, Doha, Qatar

    Abdesselam Bouzerdoum

Authors
  1. Xiaolin Tang
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  2. Son Lam Phung
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  3. Abdesselam Bouzerdoum
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  4. Van Ha Tang
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Corresponding author

Correspondence to Xiaolin Tang .

Editor information

Editors and Affiliations

  1. IIIT Hyderabad, Hyderabad, India

    C.V. Jawahar

  2. ANU, Canberra, ACT, Australia

    Hongdong Li

  3. Simon Fraser University, Burnaby, BC, Canada

    Greg Mori

  4. ETH Zurich, Zurich, Zürich, Switzerland

    Prof. Konrad Schindler

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Tang, X., Phung, S.L., Bouzerdoum, A., Tang, V.H. (2019). Pooling-Based Feature Extraction and Coarse-to-fine Patch Matching for Optical Flow Estimation. In: Jawahar, C., Li, H., Mori, G., Schindler, K. (eds) Computer Vision – ACCV 2018. ACCV 2018. Lecture Notes in Computer Science(), vol 11364. Springer, Cham. https://doi.org/10.1007/978-3-030-20870-7_37

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  • DOI: https://doi.org/10.1007/978-3-030-20870-7_37

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  • Online ISBN: 978-3-030-20870-7

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