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Background Subtraction Based on Fusion of Color and Local Patterns

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Computer Vision – ACCV 2018 (ACCV 2018)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 11366))

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Abstract

Segmentation of foreground objects using background subtraction methods is popularly used in a wide variety of application areas such as surveillance, tracking, and human pose estimation. Many of the background subtraction methods construct a background model in a pixel-wise manner using color information that is sensitive to illumination variations. In the recent past, a number of local feature descriptors have been successfully applied to overcome such issues. However, these descriptors still suffer from over-sensitivity and sometimes unable to differentiate local structures. In order to tackle the aforementioned problems of existing descriptors, we propose a novel edge based descriptor, Local Top Directional Pattern (LTDP), that represents local structures in a pattern form with aid of compass masks providing information of top local directional variations. Moreover, to strengthen the robustness of the pixel-wise background model and get benefited from each other, we combine both color and LTDP features. We evaluate the performance of our method on the publicly available change detection datasets. The results of extensive experiments demonstrate the better performance of our method compared to other state-of-the-art unsupervised methods.

This research was supported by the MSIT (Ministry of Science and ICT), Korea, under the Grand Information Technology Research Center support program (IITP-2018-2015-0-00742) supervised by the IITP (Institute for Information & Communications Technology Promotion), and the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. NRF-2015R1A2A2A01006412).

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Kyung Hee University, Yongin-si, Gyeonggi-do, 17104, Republic of Korea

    Md Rifat Arefin, Farkhod Makhmudkhujaev, Oksam Chae & Jaemyun Kim

Authors
  1. Md Rifat Arefin
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  2. Farkhod Makhmudkhujaev
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  3. Oksam Chae
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  4. Jaemyun Kim
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Corresponding author

Correspondence to Jaemyun Kim .

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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

    Konrad Schindler

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Arefin, M.R., Makhmudkhujaev, F., Chae, O., Kim, J. (2019). Background Subtraction Based on Fusion of Color and Local Patterns. In: Jawahar, C., Li, H., Mori, G., Schindler, K. (eds) Computer Vision – ACCV 2018. ACCV 2018. Lecture Notes in Computer Science(), vol 11366. Springer, Cham. https://doi.org/10.1007/978-3-030-20876-9_14

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  • DOI: https://doi.org/10.1007/978-3-030-20876-9_14

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