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An approach for moving object recognition based on BPR and CI

Author

Listed:
  • Li Wang

    (Beihang University)

  • Lida Xu

    (Beijing Jiaotong University
    Old Dominion University
    Xian Jiaotong University)

  • Renjing Liu

    (Xian Jiaotong University)

  • Hai Hong Wang

    (Qingdao University of Science and Technology)

Abstract

A recognition and classification method of multiple moving objects in traffic based on the combination of the Biomimetic Pattern Recognition (BPR) and Choquet Integral (CI) is proposed. The recognition process consists of three stages. At the first stage, vehicles and pedestrians are detected in video images and the area, the shape and the velocity features are obtained by classical methods. At the second stage, BPR is used to classify the Zernike moments extracted at the first stage. At the last stage, CI is then adopted for multi-features fusion based on the output of BPR, and the area and the velocity features obtained at the first stage to improve the recognition accuracy. Experiment results show that this approach is efficient.

Suggested Citation

  • Li Wang & Lida Xu & Renjing Liu & Hai Hong Wang, 2010. "An approach for moving object recognition based on BPR and CI," Information Systems Frontiers, Springer, vol. 12(2), pages 141-148, April.
    • Handle: RePEc:spr:infosf:v:12:y:2010:i:2:d:10.1007_s10796-008-9130-3
    DOI: 10.1007/s10796-008-9130-3
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    Cited by:

    1. Damminda Alahakoon & Rashmika Nawaratne & Yan Xu & Daswin Silva & Uthayasankar Sivarajah & Bhumika Gupta, 2023. "Self-Building Artificial Intelligence and Machine Learning to Empower Big Data Analytics in Smart Cities," Information Systems Frontiers, Springer, vol. 25(1), pages 221-240, February.
    2. Chulhwan Chris Bang, 2015. "Information systems frontiers: Keyword analysis and classification," Information Systems Frontiers, Springer, vol. 17(1), pages 217-237, February.

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