People tracking with body pose estimation for human path prediction

Photchara Ratsamee*, Yasushi Mae, Kenichi Ohara, Tomohito Takubo, Tatsuo Arai

*Corresponding author for this work

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

12 Citations (Scopus)

Abstract

Prediction and observation of human motion are essential functions for robots co-existing with humans in everyday environments. We propose a people motion tracking and prediction approach by using the advantage of detailed 3D information about the positions of body joints. Using the shoulder position displayed in a geometrical skeleton diagram of a human's upper body part, the body pose from the proposed human kinematic model is estimated. Human motion tracking and path prediction are achieved via the extended Kalman Filter. The proposed method is verified in an indoor environment where humans pass by each other. Experiment results demonstrate that walking people and their body pose are robustly tracked and predicted accurately, with less occlusions compared to traditional human tracking.

Original languageEnglish
Title of host publication2012 IEEE International Conference on Mechatronics and Automation, ICMA 2012
Pages1915-1920
Number of pages6
DOIs
Publication statusPublished - 2012
Externally publishedYes
Event2012 9th IEEE International Conference on Mechatronics and Automation, ICMA 2012 - Chengdu, China
Duration: 5 Aug 20128 Aug 2012

Publication series

Name2012 IEEE International Conference on Mechatronics and Automation, ICMA 2012

Conference

Conference2012 9th IEEE International Conference on Mechatronics and Automation, ICMA 2012
Country/TerritoryChina
CityChengdu
Period5/08/128/08/12

Keywords

  • body pose
  • path prediction and shoulder tracking

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