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A robust descriptor based on Weber's Law

9 years 3 months ago
A robust descriptor based on Weber's Law
Inspired by Weber's Law, this paper proposes a simple, yet very powerful and robust local descriptor, Weber Local Descriptor (WLD). It is based on the fact that human perception of a pattern depends on not only the change of a stimulus (such as sound, lighting, et al.) but also the original intensity of the stimulus. Specifically, WLD consists of two components: its differential excitation and orientation. A differential excitation is a function of the ratio between two terms: One is the relative intensity differences of its neighbors against a current pixel; the other is the intensity of the current pixel. An orientation is the gradient orientation of the current pixel. For a given image, we use the differential excitation and the orientation components to construct a concatenated WLD histogram feature. Experimental results on Brodatz textures show that WLD impressively outperforms the other classical descriptors (e.g., Gabor). Especially, experimental results on face detection ...
Jie Chen, Shiguang Shan, Guoying Zhao, Xilin Chen,
Added 29 May 2010
Updated 29 May 2010
Type Conference
Year 2008
Where CVPR
Authors Jie Chen, Shiguang Shan, Guoying Zhao, Xilin Chen, Wen Gao, Matti Pietikäinen
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