Bidirectional local template patterns: An effective and discriminative feature for pedestrian detection

Jiu Xu, Ning Jiang, Satoshi Goto

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

In this paper, a novel feature named bidirectional local template patterns (B-LTP) is proposed for use in pedestrian detection in still images. B-LTP is a combination and modification of two features, histogram of templates (HOT) and center-symmetric local binary patterns (CS-LBP). For each pixel, B-LTP defines four templates, each of which contains the pixel itself and two neighboring center-symmetric pixels. For each template, it then calculates information from the relationships among these three pixels and from the two directional transitions across these pixels. Moreover, because the feature length of B-LTP is small, it consumes less memory and computational power. Experimental results on an INRIA dataset show that the speed and detection rate of our proposed B-LTP feature outperform those of other features such as histogram of orientated gradient (HOG), HOT, and covariance matrix (COV).

Original languageEnglish
Pages (from-to)1204-1213
Number of pages10
JournalIEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
VolumeE96-A
Issue number6
DOIs
Publication statusPublished - 2013 Jun

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Keywords

  • Bidirectional local template patterns
  • Feature extraction
  • Pedestrian detection
  • Support vector machine

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Computer Graphics and Computer-Aided Design
  • Applied Mathematics
  • Signal Processing

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