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Robust background maintenance by estimating global intensity level changes for dynamic scenes

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Abstract

The maintenance of relevant backgrounds under various scene changes is very crucial to detect foregrounds robustly. We propose a background maintenance method for dynamic scenes including global intensity level changes caused by changes of illumination conditions and camera settings. If the global level of the intensity changes abruptly, the conventional background models cannot discriminate true foreground pixels from the background. The proposed method adaptively modifies the background model by estimating the level changes. Because there are changes caused by moving objects as well as global intensity level changes, we estimate the dominant level change over the whole image regions by mean shift. Then, the problem caused by saturated pixels are handled by an additional scheme. In the experiments for dynamic scenes, our proposed method outperforms previous methods by adaptive background maintenance and handling of saturated pixels.

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Authors and Affiliations

  1. Department of Electrical Engineering, KAIST, 373-1 Guseong-dong, Yuseong-gu, Daejeon, 305-701, Republic of Korea

    Youngbae Hwang & In-So Kweon

  2. Hyundai Motor Company, Jangdeok-dong, Hwaseong-si, Gyeonggi-do, Republic of Korea

    Kapje Sung

  3. Agency for Defense Development, Sunam-dong, Yuseong-gu, Daejeon, Republic of Korea

    Jeong Sook Chae & Yong Woon Park

Authors
  1. Youngbae Hwang
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  2. Kapje Sung
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  3. Jeong Sook Chae
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  4. Yong Woon Park
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  5. In-So Kweon
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Correspondence to Youngbae Hwang.

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Hwang, Y., Sung, K., Chae, J.S. et al. Robust background maintenance by estimating global intensity level changes for dynamic scenes. Intel Serv Robotics 2, 187–194 (2009). https://doi.org/10.1007/s11370-009-0044-9

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  • DOI: https://doi.org/10.1007/s11370-009-0044-9

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