Local Binary Patterns with mahalanobis distance maps for human detection

Xiangjian He, Jianmin Li, Yan Chen

Research output: Chapter in Book/Conference proceedingConference contributionpeer-review

4 Citations (Scopus)

Abstract

Local Binary Pattern (LBP) was designed and has been widely used for efficient texture classification. LBP provides a simple and effective way to represent texture patterns. Uniform LBPs play an important role for LBP-based pattern/object recognition as they include majority of LBPs. On the other hand, Human detection based on Mahalanobis Distance Map (MDM) recognizes appearance of human based on geometrical structure. Each MDM shows a clear texture pattern that can be classified using LBPs. Ln this paper, we compute LBPs of MDMs. Chi-square as a measure is used for human detection based on uniform LBPs obtained. We show that our method using LBPs built on MDMs has a higher human detection rate and a lower false positive rate compared to the method merely based on MDMs.

Original languageEnglish
Title of host publicationProceedings - 1st International Congress on Image and Signal Processing, CISP 2008
Pages520-524
Number of pages5
DOIs
Publication statusPublished - 2008
Externally publishedYes
Event1st International Congress on Image and Signal Processing, CISP 2008 - Sanya, Hainan, China
Duration: 27 May 200830 May 2008

Publication series

NameProceedings - 1st International Congress on Image and Signal Processing, CISP 2008
Volume2

Conference

Conference1st International Congress on Image and Signal Processing, CISP 2008
Country/TerritoryChina
CitySanya, Hainan
Period27/05/0830/05/08

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Signal Processing

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