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Proceedings Paper

Applied learning-based color tone mapping for face recognition in video surveillance system
Author(s): Chuu Tian Yew; Shahrel Azmin Suandi
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Paper Abstract

In this paper, we present an applied learning-based color tone mapping technique for video surveillance system. This technique can be applied onto both color and grayscale surveillance images. The basic idea is to learn the color or intensity statistics from a training dataset of photorealistic images of the candidates appeared in the surveillance images, and remap the color or intensity of the input image so that the color or intensity statistics match those in the training dataset. It is well known that the difference in commercial surveillance cameras models, and signal processing chipsets used by different manufacturers will cause the color and intensity of the images to differ from one another, thus creating additional challenges for face recognition in video surveillance system. Using Multi-Class Support Vector Machines as the classifier on a publicly available video surveillance camera database, namely SCface database, this approach is validated and compared to the results of using holistic approach on grayscale images. The results show that this technique is suitable to improve the color or intensity quality of video surveillance system for face recognition.

Paper Details

Date Published: 8 June 2012
PDF: 5 pages
Proc. SPIE 8334, Fourth International Conference on Digital Image Processing (ICDIP 2012), 833435 (8 June 2012); doi: 10.1117/12.956485
Show Author Affiliations
Chuu Tian Yew, Univ. Sains Malaysia (Malaysia)
Shahrel Azmin Suandi, Univ. Sains Malaysia (Malaysia)

Published in SPIE Proceedings Vol. 8334:
Fourth International Conference on Digital Image Processing (ICDIP 2012)
Mohamed Othman; Sukumar Senthilkumar; Xie Yi, Editor(s)

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