Object tracking using improved Camshift with SURF method

Jianhong Li*, Ji Zhang, Zhenhuan Zhou, Wei Guo, Bo Wang, Qingjie Zhao

*Corresponding author for this work

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

16 Citations (Scopus)

Abstract

Camshift is an effective algorithm for real time dynamic target tracking applications, which only uses color features and is sensitive to illumination and some other environment factors. When similar color existing in the background, traditional Camshift algorithm may fail, that is the target getting lost. To solve the problem, an improved Camshift algorithm is firstly proposed in this paper to reduce the influence of illumination interference. Besides, a method judging whether the target is lost is also proposed. Once the target is judged lost, the Speeded Up Robust Features (SURF) is utilized to find it again and the improved Camshift keeps on tracking the target continuously. SURF is invariant to scale, rotation and translation of images. We program in C++ based on OpenCV. The results prove that the proposed method is more robust than the traditional Camshift and give better tracking performance than some other improved methods.

Original languageEnglish
Title of host publicationProceedings - 2011 IEEE International Workshop on Open-Source Software for Scientific Computation, OSSC-2011
Pages136-141
Number of pages6
DOIs
Publication statusPublished - 2011
Event2011 IEEE International Workshop on Open-Source Software for Scientific Computation, OSSC-2011 - Beijing, China
Duration: 12 Oct 201114 Oct 2011

Publication series

NameProceedings - 2011 IEEE International Workshop on Open-Source Software for Scientific Computation, OSSC-2011

Conference

Conference2011 IEEE International Workshop on Open-Source Software for Scientific Computation, OSSC-2011
Country/TerritoryChina
CityBeijing
Period12/10/1114/10/11

Keywords

  • SURF
  • improved Camshift
  • target tracking

Fingerprint

Dive into the research topics of 'Object tracking using improved Camshift with SURF method'. Together they form a unique fingerprint.

Cite this