Improved tracking-learning-detection human tracking algorithm

Yan Liang*, Feng Pan, Bo Yang, Weixing Li

*Corresponding author for this work

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

Abstract

For the problem that appearance of human will be changed in motion, it is a challenge to those capabilities of tracker, related to adaptation of human appearance. In the paper, an improved Tracking-Learning-Detection algorithm, including short-term-tracking, real-time-detection and online-learning, is proposed. Furthermore, scale-invariant feature is applied to the short-term-tracking to determine the location of target in consecutive frames. The video stream of the PETS2006 database is utilized to evaluate the proposed algorithm. Experiments results demonstrate the effectiveness, especially on the short-term-tracking performance.

Original languageEnglish
Title of host publicationInformation Technology Applications in Industry
PublisherTrans Tech Publications Ltd.
Pages2631-2634
Number of pages4
EditionPART 1
ISBN (Print)9783037855744
DOIs
Publication statusPublished - 2013
Event2012 International Conference on Information Technology and Management Innovation, ICITMI 2012 - Guangzhou, China
Duration: 10 Nov 201211 Nov 2012

Publication series

NameApplied Mechanics and Materials
NumberPART 1
Volume263-266
ISSN (Print)1660-9336
ISSN (Electronic)1662-7482

Conference

Conference2012 International Conference on Information Technology and Management Innovation, ICITMI 2012
Country/TerritoryChina
CityGuangzhou
Period10/11/1211/11/12

Keywords

  • Human tracking
  • Scale-invariant feature
  • Tracking-learning-detection

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