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Chinese Conference on Pattern Recognition

CCPR 2016: Pattern Recognition pp 304–317Cite as

Video Object Detection and Segmentation Based on Proposal Boxes

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 662))

Abstract

In this paper, we propose a new method to detect and segment foreground object in video automatically. Given a video sequence, our method begins by generating proposal bounding boxes in each frame, according to both static and motion cues. The boxes are used to detect the primary object in the sequence. We measure each box with its likelihood of containing a foreground object, connect boxes in adjacent frames and calculate the similarity between them. A layered Directed Acyclic Graph is constructed to select object box in each frame. With the help of the object boxes, we model the motion and appearance of the object. Motion cues and appearance cues are combined into an energy minimization framework to obtain the coherent foreground object segmentation in the whole video. Our method reports comparable results with state-of-the-art works on challenging benchmark dataset.

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Acknowledgements

This work was supported by the National High-Tech R&D Program of China (863 Program) under Grant 2015AA015904.

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Authors and Affiliations

  1. National Key Laboratory of Science and Technology on Multi-Spectral Information Processing, School of Automation, Huazhong University of Science and Technology, Wuhan, China

    Xiaodi Zhang, Zhiguo Cao, Yang Xiao & Furong Zhao

Authors
  1. Xiaodi Zhang
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  2. Zhiguo Cao
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  3. Yang Xiao
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  4. Furong Zhao
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Corresponding author

Correspondence to Zhiguo Cao .

Editor information

Editors and Affiliations

  1. Institute of Automation, Chinese Academy of Sciences, Beijing, China

    Tieniu Tan

  2. Xi’an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi'an, China

    Xuelong Li

  3. Chinese Academy of Sciences, Institute of Computing Technology, Beijing, China

    Xilin Chen

  4. Tsinghua University , Beijing, China

    Jie Zhou

  5. Nanjing University of Science and Technology, Nanjing, China

    Jian Yang

  6. University of Electronic Science and Technology, Chengdu, Sichuan, China

    Hong Cheng

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© 2016 Springer Nature Singapore Pte Ltd.

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Zhang, X., Cao, Z., Xiao, Y., Zhao, F. (2016). Video Object Detection and Segmentation Based on Proposal Boxes. In: Tan, T., Li, X., Chen, X., Zhou, J., Yang, J., Cheng, H. (eds) Pattern Recognition. CCPR 2016. Communications in Computer and Information Science, vol 662. Springer, Singapore. https://doi.org/10.1007/978-981-10-3002-4_26

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  • DOI: https://doi.org/10.1007/978-981-10-3002-4_26

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-3001-7

  • Online ISBN: 978-981-10-3002-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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