Abstract
In this paper, we propose a multi-scale integral modified census transform (MsiMCT) for eye detection. Modified census transform shows a good classification performance. However, it does not represent block properties. We therefore consider a method for overcoming this limitation. First, we propose the integral modified census transform (iMCT) using integral images, which can compute the mean intensity of the rectangular region rapidly. Using iMCT, we propose the multi-scale integral modified census transform (MsiMCT), which is structured as a concatenation of various iMCTs. The proposed MsiMCT can describe from pixel features to block features, and can therefore be implemented in many applications, such as face detection and human body detection, without modification. Our experimental results using various images show that the proposed method provides good detection accuracy, in terms of the detection rate of the number of selected weak classifiers.
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Choi, I., Kim, D. (2012). Multi-scale Integral Modified Census Transform for Eye Detection. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2012. Lecture Notes in Computer Science, vol 7432. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33191-6_5
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DOI: https://doi.org/10.1007/978-3-642-33191-6_5
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-33190-9
Online ISBN: 978-3-642-33191-6
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