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A Message Passing Algorithm for MRF Inference with Unknown Graphs and Its Applications

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Computer Vision -- ACCV 2014 (ACCV 2014)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 9006))

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Abstract

Recent research shows that estimating labels and graph structures simultaneously in Markov random Fields can be achieved via solving LP problems. The scalability is a bottleneck that prevents applying such technique to larger problems such as image segmentation and object detection. Here we present a fast message passing algorithm based on the mixed-integer bilinear programming formulation of the original problem. We apply our algorithm to both synthetic data and real-world applications. It compares favourably with previous methods.

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Notes

  1. 1.

    To compute these features, we need low-level image descriptors. All evaluating methods using the potential function (18) use the same descriptors extracted by us.

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Acknowledgement

We thank Qinfeng Shi for his suggestion on the exposition of this paper. We thank Cesar Dario Cadena Lerma for his help on using the KITTI dataset. This work was supported by a grant from the National High Technology Research and Development Program of China (863 Program) (No. 2013AA10230402), and a grant from the Fundamental Research Funds of Northwest A&F University (No. QN2013056).

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Authors and Affiliations

  1. School of Computer Science, The University of Adelaide, Adelaide, Australia

    Zhenhua Wang

  2. College of Information Engineering, Northwest A&F University, Yangling District, China

    Zhenhua Wang, Zhiyi Zhang & Nan Geng

Authors
  1. Zhenhua Wang
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  2. Zhiyi Zhang
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  3. Nan Geng
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Corresponding author

Correspondence to Zhiyi Zhang .

Editor information

Editors and Affiliations

  1. Technische Universität München, Garching, Bayern, Germany

    Daniel Cremers

  2. University of Adelaide, Adelaide, South Australia, Australia

    Ian Reid

  3. Keio University, Yokohama, Kanagawa, Japan

    Hideo Saito

  4. University of California at Merced, Merced, California, USA

    Ming-Hsuan Yang

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© 2015 Springer International Publishing Switzerland

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Wang, Z., Zhang, Z., Geng, N. (2015). A Message Passing Algorithm for MRF Inference with Unknown Graphs and Its Applications. In: Cremers, D., Reid, I., Saito, H., Yang, MH. (eds) Computer Vision -- ACCV 2014. ACCV 2014. Lecture Notes in Computer Science(), vol 9006. Springer, Cham. https://doi.org/10.1007/978-3-319-16817-3_19

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  • DOI: https://doi.org/10.1007/978-3-319-16817-3_19

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-16816-6

  • Online ISBN: 978-3-319-16817-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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