Keyframe selection for motion capture using motion activity analysis

Ming Hwa Kim, Lap Pui Chau, Wan Chi Siu

Research output: Unpublished conference presentation (presented paper, abstract, poster)Conference presentation (not published in journal/proceeding/book)Academic researchpeer-review

9 Citations (Scopus)


Motion capture data acquired from high definition cameras creates accurate human motion representation but introduces many redundant frames which pose a problem in data storage and motion retrieval purposes. In this paper, a keyframing approach is proposed to reduce the motion data by extracting keyframes using motion analysis approach in sampling windows. Motion changes in sampling windows for original motion without frame skipping and with frame skipping are computed. The difference in the motion changes is the main aspect in deciding whether the frames in sampling windows are possible candidates for keyframe selection. Simulation results showed that the proposed method is able to achieve an overall good visual quality for different types of motion. It also gives an improvement of up to 52% in terms of mean square error measurement, as compared to the existing keyframe extraction method, which is curve simplification method.

Original languageEnglish
Number of pages4
Publication statusPublished - May 2012
Event2012 IEEE International Symposium on Circuits and Systems, ISCAS 2012 - Seoul, Korea, Republic of
Duration: 20 May 201223 May 2012


Conference2012 IEEE International Symposium on Circuits and Systems, ISCAS 2012
Country/TerritoryKorea, Republic of

ASJC Scopus subject areas

  • Hardware and Architecture
  • Electrical and Electronic Engineering


Dive into the research topics of 'Keyframe selection for motion capture using motion activity analysis'. Together they form a unique fingerprint.

Cite this