Compositional interaction descriptor for human interaction recognition

Nam Gyu Cho, Se Ho Park, Jeong Seon Park, Unsang Park, Seong Whan Lee

Research output: Contribution to journalArticlepeer-review

21 Citations (Scopus)


In this paper, we address the problem of human interaction recognition. We propose a novel compositional interaction descriptor to represent complex human interactions containing high intra and inter-class variations. The compositional interaction descriptor represents motion relationships on individual, local, and global levels to build a highly discriminative description. We evaluate the proposed method using UT-Interaction and BIT-Interaction public benchmark datasets. Experimental results demonstrate that the performance of the proposed approach is on a par with previous methods.

Original languageEnglish
Pages (from-to)169-181
Number of pages13
Publication statusPublished - 2017 Dec 6


  • Compositional interaction descriptor
  • Human interaction recognition
  • Human motion analysis

ASJC Scopus subject areas

  • Computer Science Applications
  • Cognitive Neuroscience
  • Artificial Intelligence


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