Evaluating human motion complexity based on un-correlation and non-smoothness

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)peer-review

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Detail(s)

Original languageEnglish
Title of host publicationAdvances in Multimedia Information Processing, PCM 2010
Subtitle of host publication11th Pacific Rim Conference on Multimedia, Proceedings
PublisherSpringer Verlag
Pages538-548
Volume6298 LNCS
EditionPART 2
ISBN (Print)3642156959, 9783642156953
Publication statusPublished - 2010

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6298 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Title11th Pacific Rim Conference on Multimedia, PCM 2010
PlaceChina
CityShanghai
Period21 - 24 September 2010

Abstract

Determining the complexity of a human motion is useful for human motion analysis with potential applications such as biomechanics, sport training, entertainment. There has not been much research effort in finding a complexity measure to evaluate the whole human body motion automatically. In this paper, we present a novel approach to evaluate the complexity of human motion based on motion captured data. Our proposed complexity measure considers the un-correlation among active joint dimensions and the non-smoothness of each joint dimension in the temporal direction. It is logical to expect that a motion is more complex if the joint dimensions are less correlated and the temporal movement is less smooth. The experimental results show that our proposed complexity measure is able to cluster the same type of motions and differentiate motions with different observed complexities. © 2010 Springer-Verlag.

Research Area(s)

  • motion analysis, Motion capture, motion complexity, non-smoothness, un-correlation

Citation Format(s)

Evaluating human motion complexity based on un-correlation and non-smoothness. / Yang, Yang; Leung, Howard; Yue, Lihua; Deng, Liqun.

Advances in Multimedia Information Processing, PCM 2010: 11th Pacific Rim Conference on Multimedia, Proceedings. Vol. 6298 LNCS PART 2. ed. Springer Verlag, 2010. p. 538-548 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6298 LNCS).

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)peer-review