HUMAN DETECTION USING SPARSE REPRESENTATION

被引：0

作者：

Vinay, G. Krishna ^{[1
]}

Haque, S. M. ^{[2
]}

Babu, R. Venkatesh ^{[3
]}

Ramakrishnan, K. R. ^{[1
]}

机构：

[1] Indian Inst Sci, Dept Elect Engn, Bangalore 560012, Karnataka, India

[2] Indian Inst Sci, Dept Elect Commun Engn, Bangalore, Karnataka, India

[3] Indian Inst Sci, Supercomp Educ & Res Ctr, Bangalore, Karnataka, India

来源：

2012 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP) | 2012年

关键词：

Human Detection; Histogram of Oriented Gradients(HOG); l(1)-norm minimization; Sparse representation; Scale-embedded Dictionary;

D O I：

暂无

中图分类号：

O42 [声学];

学科分类号：

070206 ; 082403 ;

摘要：

The problem of human detection is challenging, more so, when faced with adverse conditions such as occlusion and background clutter. This paper addresses the problem of human detection by representing an extracted feature of an image using a sparse linear combination of chosen dictionary atoms. The detection along with the scale finding, is done by using the coefficients obtained from sparse representation. This is of particular interest as we address the problem of scale using a scale-embedded dictionary where the conventional methods detect the object by running the detection window at all scales.

引用

页码：1513 / 1516

页数：4

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