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Multi-context Fusion Based Robust Face Detection in Dynamic Environments

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Fuzzy Systems and Knowledge Discovery (FSKD 2005)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3613))

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Abstract

We propose a method of multiple context fusion based robust face detection scheme. It takes advantage of multiple contexts by combining color, illumination (brightness and light direction), spectral composition(texture) for environment awareness. It allows the object detection scheme can react in a robust way against dynamically changing environment. Multiple context based face detection is attractive since it could accumulate face model by autonomous learning process for each environment context category. This approach can be easily used in searching for multiple scale faces by scaling up/down the input image with some factor. The proposed face detection using the multiple context fusion shows more stability under changing environments than other detection methods. We employ Fuzzy ART for the multiple context- awareness. The proposed face detection achieves the capacity of the high level attentive process by taking advantage of the context-awareness using the information from illumination, color, and texture. We achieve very encouraging experimental results, especially when operation environment varies dynamically.

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© 2005 Springer-Verlag Berlin Heidelberg

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Nam, M.Y., Rhee, P.K. (2005). Multi-context Fusion Based Robust Face Detection in Dynamic Environments. In: Wang, L., Jin, Y. (eds) Fuzzy Systems and Knowledge Discovery. FSKD 2005. Lecture Notes in Computer Science(), vol 3613. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11539506_87

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  • DOI: https://doi.org/10.1007/11539506_87

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-28312-6

  • Online ISBN: 978-3-540-31830-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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