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EBE: Elastic blob ensemble for coarse human tracking

  • CNRS SAMOVAR UMR 5157
  • Gdańsk University of Technology

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

Abstract

We propose a novel probabilistic tracking algorithm based on an elastic blob ensemble (EBE) which is applicable to track flexible objects. It outputs a coarse motion cue in the form of the object's location and orientation together with the location of the blobs. The main assumption is that the orientation of the whole object does not change much between neighboring frames. A discrete solution space is created in the current frame around the blobs' positions from the previous frame. Our model then promotes solutions whose orientations are close to the prior orientation, which match the modeled to the observed appearance well, and which follow modeled spatial configuration. It combines the strengths of three popular approaches to visual tracking : mean-shift tracker, particle filtering, and pictorial structures. As a result, the proposed framework tracks human upper body composed of head, torso, and hips at the rate of 40 fps on a regular desktop PC.

Original languageEnglish
Title of host publication2012 IEEE International Conference on Image Processing, ICIP 2012 - Proceedings
Pages1625-1628
Number of pages4
DOIs
Publication statusPublished - 1 Dec 2012
Externally publishedYes
Event2012 19th IEEE International Conference on Image Processing, ICIP 2012 - Lake Buena Vista, FL, United States
Duration: 30 Sept 20123 Oct 2012

Publication series

NameProceedings - International Conference on Image Processing, ICIP
ISSN (Print)1522-4880

Conference

Conference2012 19th IEEE International Conference on Image Processing, ICIP 2012
Country/TerritoryUnited States
CityLake Buena Vista, FL
Period30/09/123/10/12

Keywords

  • Kernel collaboration
  • blob tracking
  • mean-shift tracking
  • pictorial structures

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