Recognition of human group activity for video analytics

Jaeyong Ju, Cheoljong Yang, Sebastian Scherer, Hanseok Ko

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Human activity recognition is an important and challenging task for video content analysis and understanding. Individual activity recognition has been well studied recently. However, recognizing the activities of human group with more than three people having complex interactions is still a formidable challenge. In this paper, a novel human group activity recognition method is proposed to deal with complex situation where there are multiple sub-groups. To characterize the inherent interactions of intra-subgroups and inter-subgroups with the varying number of participants, this paper proposes three types of group-activity descriptor using motion trajectory and appearance information of people. Experimental results on a public human group activity dataset demonstrate effectiveness of the proposed method.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
PublisherSpringer Verlag
Pages161-169
Number of pages9
Volume9315
ISBN (Print)9783319240770
DOIs
Publication statusPublished - 2015
Event16th Pacific-Rim Conference on Multimedia, PCM 2015 - Gwangju, Korea, Republic of
Duration: 2015 Sep 162015 Sep 18

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9315
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other16th Pacific-Rim Conference on Multimedia, PCM 2015
CountryKorea, Republic of
CityGwangju
Period15/9/1615/9/18

Keywords

  • Activity recognition
  • Human group activity
  • Video analytics

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Fingerprint Dive into the research topics of 'Recognition of human group activity for video analytics'. Together they form a unique fingerprint.

  • Cite this

    Ju, J., Yang, C., Scherer, S., & Ko, H. (2015). Recognition of human group activity for video analytics. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9315, pp. 161-169). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9315). Springer Verlag. https://doi.org/10.1007/978-3-319-24078-7_16