Blob tracking with adaptive feature selection and accurate scale determination

Jingping Jia, David Feng, Yanmei Chai, Rongchun Zhao, Zheru Chi

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review


We propose a novel color based tracking framework in which an object configuration and color feature are simultaneously determined via scale space filtration. The tracker can automatically select discriminative color feature that well distinguishes foreground from background. According to that feature, a likelihood image of the target is generated for each incoming frame. The target's area turns into a blob in the likelihood image. The scale of this blob can be determined based on the local maximum of differential scale-space filters. We employ the QP_TR trust region algorithm to search for the local maximum of multi-scale normalized Laplacian filter of the likelihood image to locate the target as well as determine its scale. Based on the tracking results of sequence examples, the proposed method has been proven to be resilient to the color and lighting changes, be capable of describing the target more accurately and achieve much better tracking precision.
Original languageEnglish
Title of host publicationAdvances in Visual Computing - Second International Symposium, ISVC 2006, Proceedings
PublisherSpringer Verlag
Number of pages10
ISBN (Print)3540486283, 9783540486282
Publication statusPublished - 1 Jan 2006
Event2nd International Symposium on Visual Computing, ISVC 2006 - Lake Tahoe, NV, United States
Duration: 6 Nov 20068 Nov 2006

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4291 LNCS - I
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference2nd International Symposium on Visual Computing, ISVC 2006
Country/TerritoryUnited States
CityLake Tahoe, NV

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


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