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Local structured representation for generic object detection

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Abstract

Structure information plays an important role in both object recognition and detection. This paper studies what visual structure is and addresses the problem of structure modeling and representation from two aspects: visual feature and topology model. Firstly, at feature level, we propose Local Structured Descriptor to capture the object’s local structure effectively, and develop the descriptors from shape and texture information, respectively. Secondly, at topology level, we present a local structured model with a boosted feature selection and fusion scheme. All experiments are conducted on the challenging PASCAL Visual Object Classes (VOC) datasets from VOC2007 to VOC2010. Experimental results show that our method achieves very competitive performance.

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Acknowledgements

This work was funded by the National Basic Research Program of China (2012CB316302), the National Natural Science Foundation of China (Grant Nos. 61403387, 61322209 and 61175007), the Strategic Priority Research Program of the Chinese Academy of Sciences (XDA06040102).

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Authors and Affiliations

  1. Center for Research on Intelligent Perception and Computing, Chinese Academy of Sciences, Beijing, 100190, China

    Junge Zhang, Kaiqi Huang & Tieniu Tan

  2. Research Center for Brain-inspired Intelligence, Chinese Academy of Sciences, Beijing, 100190, China

    Kaiqi Huang, Tieniu Tan & Zhaoxiang Zhang

  3. National Laboratory of Pattern Recognition Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China

    Junge Zhang, Kaiqi Huang, Tieniu Tan & Zhaoxiang Zhang

Authors
  1. Junge Zhang
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  2. Kaiqi Huang
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  3. Tieniu Tan
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  4. Zhaoxiang Zhang
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Correspondence to Junge Zhang.

Additional information

Junge Zhang received his PhD in pattern recognition and intelligent systems from Institute of Automation, Chinese Academy of Sciences (CASIA), China in 2013. In July 2013, he joined the Center for Research on Intelligent Perception and Computing (CRIPAC), China, as an assistant professor. His major research interests include computer vision, pattern recognition. He served as the publicity chair and the technical program committee member of several conferences, and the peer reviewer of over 10 international journals and conferences. In 2010 and 2011, he and his group members won the champion of PASCAL VOC challenge on object detection and ranked the second on object classification.

Kaiqi Huang received his MS in electrical engineering from Nanjing University of Science and Technology, China, and PhD in signal and information processing from Southeast University, China. After receiving the PhD, he became a postdoctoral researcher with the National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, China where he is currently a professor. He has published over 100 papers on TPAMI, TIP, TCSVT, TSMCB, CVIU, Pattern Recognition and CVPR, ECCV. He is senior member of IEEE and the Deputy Secretary General of the IEEE Beijing Section. His interests include visual surveillance, image and video analysis, human vision and cognition, computer vision, etc.

Tieniu Tan received his BS in electronic engineering from Xi’an Jiaotong University, China in 1984, and his MS and PhD in electronic engineering from Imperial College London, UK in 1986 and 1989, respectively. In January 1998, he returned to China to join the National Laboratory of Pattern Recognition (NLPR), Institute of Automation of the Chinese Academy of Sciences (CAS), China as a full professor. He is currently the director of Center for Research on Intelligent Perception and Computing at the Institute of Automation, China, and also serves as the vice president of CAS. His current research interests include biometrics, image and video understanding, and information forensics and security.

Zhaoxiang Zhang received his BS in circuits and systems from the University of Science and Technology of China, China in 2004. After that, he was a PhD candidate under the supervision of Professor Tieniu Tan in the National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences (CAS), China, where he received his PhD in 2009. In October 2009, he joined the School of Computer Science and Engineering, Beihang University, China as an assistant professor (2009–2011), an associate professor (2012–2015) and the vise-director of the Department of Computer application technology (2014–2015). In July 2015, he returned to the Institute of Automation, CAS. He is now a professor in the Research Center for Brain-inspired Intelligence.

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Zhang, J., Huang, K., Tan, T. et al. Local structured representation for generic object detection. Front. Comput. Sci. 11, 632–648 (2017). https://doi.org/10.1007/s11704-016-5530-6

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