IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
Online ISSN : 1745-1337
Print ISSN : 0916-8508
Special Section on Image Media Quality
Human Detection Method Based on Non-Redundant Gradient Semantic Local Binary Patterns
Jiu XUNing JIANGWenxin YUHeming SUNSatoshi GOTO
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2015 Volume E98.A Issue 8 Pages 1735-1742

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Abstract

In this paper, a feature named Non-Redundant Gradient Semantic Local Binary Patterns (NRGSLBP) is proposed for human detection as a modified version of the conventional Semantic Local Binary Patterns (SLBP). Calculations of this feature are performed for both intensity and gradient magnitude image so that texture and gradient information are combined. Moreover, and to the best of our knowledge, non-redundant patterns are adopted on SLBP for the first time, allowing better discrimination. Compared with SLBP, no additional cost of the feature dimensions of NRGSLBP is necessary, and the calculation complexity is considerably smaller than that of other features. Experimental results on several datasets show that the detection rate of our proposed feature outperforms those of other features such as Histogram of Orientated Gradient (HOG), Histogram of Templates (HOT), Bidirectional Local Template Patterns (BLTP), Gradient Local Binary Patterns (GLBP), SLBP and Covariance matrix (COV).

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© 2015 The Institute of Electronics, Information and Communication Engineers
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