Whole body motion primitive segmentation from monocular video

Dana Kulić, Dongheui Lee, Yoshihiko Nakamura

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

11 Citations (Scopus)


This paper proposes a novel approach for motion primitive segmentation from continuous full body human motion captured on monocular video. The proposed approach does not require a kinematic model of the person, nor any markers on the body. Instead, optical flow computed directly in the image plane is used to estimate the location of segment points. The approach is based on detecting tracking features in the image based on the Shi and Thomasi algorithm [1]. The optical flow at each feature point is then estimated using the Lucas Kanade Pyramidal Optical Flow estimation algorithm [2]. The feature points are clustered and tracked on-line to find regions of the image with coherent movement. The appearance and disappearance of these coherent clusters indicates the start and end points of motion primitive segments. The algorithm performance is validated on full body motion video sequences, and compared to a joint-angle, motion capture based approach. The results show that the segmentation performance is comparable to the motion capture based approach, while using much simpler hardware and at a lower computational effort.

Original languageEnglish
Title of host publication2009 IEEE International Conference on Robotics and Automation, ICRA '09
PublisherIEEE, Institute of Electrical and Electronics Engineers
Number of pages7
ISBN (Print)9781424427895
Publication statusPublished - 2 Nov 2009
Externally publishedYes
EventIEEE International Conference on Robotics and Automation 2009 - Kobe, Japan
Duration: 12 May 200917 May 2009
https://ieeexplore.ieee.org/xpl/conhome/5076472/proceeding (Proceedings)

Publication series

NameProceedings - IEEE International Conference on Robotics and Automation
ISSN (Print)1050-4729


ConferenceIEEE International Conference on Robotics and Automation 2009
Abbreviated titleICRA 2009
Internet address

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