Particle filter based human motion tracking

Zhenning Li, Dana Kulić

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

4 Citations (Scopus)

Abstract

This paper proposes a particle filter based markerless upper body motion capture system, capable of running in realtime. This system is designed for a humanoid robot application, and thus a monocular image sequence is used as input. We first set up a model of the human body, a sub-model which includes 11 Degrees of Freedom is used for the upper body tracking. Considering the realtime processing requirements, two time efficient cues are implemented in the likelihood calculation, namely the edge cue and the distance cue. The system is tested using a publicly available database, which consists of both the videos and the ground truth data, enabling quantitative error analysis. The system successfully tracks the human through arbitrary upper body motion at 20Hz.

Original languageEnglish
Title of host publication11th International Conference on Control, Automation, Robotics and Vision, ICARCV 2010
Pages555-560
Number of pages6
DOIs
Publication statusPublished - 1 Dec 2010
Externally publishedYes
EventInternational Conference on Control, Automation, Robotics and Vision 2010 - Singapore, Singapore
Duration: 7 Dec 201010 Dec 2010
Conference number: 11th
https://ieeexplore.ieee.org/xpl/conhome/5702939/proceeding (Proceedings)

Publication series

Name11th International Conference on Control, Automation, Robotics and Vision, ICARCV 2010

Conference

ConferenceInternational Conference on Control, Automation, Robotics and Vision 2010
Abbreviated titleICARV 2010
CountrySingapore
CitySingapore
Period7/12/1010/12/10
Internet address

Keywords

  • Human motion capture
  • Marker-less
  • Particle filter
  • Quantitative error analysis
  • Realtime

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