A modified Mahalanobis distance for human detection in out-door environments

Yan Chen, Qiang Wu, Xiangjian He, Wenjing Jia, Tom Hintz

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

2 Citations (Scopus)

Abstract

This paper proposes a novel method for human detection from static images based on pixel structure of input images. Each image is divided into four parts, and a weight is assigned to each part of the image. In training stage, all sample images including human images and non-human images are used to construct a Mahalanobis distance map through statistically analyzing the difference between the different blocks on each original image. A projection matrix will be created with Linear Discriminant Method (LDM) based on the Mahalanobis distance map. This projection matrix will be used to transform multidimensional feature vectors into one dimensional feature domain according to a pre-calculated threshold to distinguish human figures from non-human figures. In comparison with the method without introducing weights, the proposed method performs much better. Encouraging experimental results have been obtained based on MIT dataset and our own dataset.

Original languageEnglish
Title of host publicationProceedings - 2008 the 1st IEEE International Conference on Ubi-Media Computing and Workshops, U-Media2008
Pages243-248
Number of pages6
DOIs
Publication statusPublished - 2008
Externally publishedYes
Event2008 the 1st IEEE International Conference on Ubi-Media Computing and Workshops, U-Media2008 - Lanzhou University, China
Duration: 31 Jul 20081 Aug 2008

Publication series

NameProceedings - 2008 the 1st IEEE International Conference on Ubi-Media Computing and Workshops, U-Media2008

Conference

Conference2008 the 1st IEEE International Conference on Ubi-Media Computing and Workshops, U-Media2008
Country/TerritoryChina
CityLanzhou University
Period31/07/081/08/08

ASJC Scopus subject areas

  • Computer Science Applications
  • Software

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