A real-time tracking algorithm based on gray distribution and distance kernel space

Weixing Li*, Yating Xiao, Feng Pan, Kai Zhou

*Corresponding author for this work

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

Abstract

The application of the traditional Camshift algorithm, which exhibits a good tracking performance in case of the obvious color characters, meanwhile, is limited in the target tracking in the color space. A fast tracking algorithm based on gray value distribution and distance kernel space is proposed. A 1.5D gray histogram method is designed to describe the model of moving object, which improves the reduction of computation for the back projection and real-time tracking performance. Moreover, a distance kernel function, describing the object weights, is constructed so as to handle the background disturbance and occlusion problem. Experiment results demonstrate the efficiency of proposed algorithm, that it can achieve a fast object tracking and resist background disturbance in some level.

Original languageEnglish
Title of host publicationProceedings of 2013 Chinese Intelligent Automation Conference - Intelligent Information Processing
Pages197-204
Number of pages8
DOIs
Publication statusPublished - 2013
Event2013 Chinese Intelligent Automation Conference, CIAC 2013 - Yangzhou, Jiangsu, China
Duration: 23 Aug 201325 Aug 2013

Publication series

NameLecture Notes in Electrical Engineering
Volume256 LNEE
ISSN (Print)1876-1100
ISSN (Electronic)1876-1119

Conference

Conference2013 Chinese Intelligent Automation Conference, CIAC 2013
Country/TerritoryChina
CityYangzhou, Jiangsu
Period23/08/1325/08/13

Keywords

  • Camshift
  • Kernel space
  • Object
  • Spatial histogram
  • Tracking

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