Detailed Information

Cited 0 time in webofscience Cited 0 time in scopus
Metadata Downloads

Compositional interaction descriptor for human interaction recognition

Authors
Cho, Nam-GyuPark, Se-HoPark, Jeong-SeonPark, UnsangLee, Seong-Whan
Issue Date
6-12월-2017
Publisher
ELSEVIER
Keywords
Human interaction recognition; Compositional interaction descriptor; Human motion analysis
Citation
NEUROCOMPUTING, v.267, pp.169 - 181
Indexed
SCIE
SCOPUS
Journal Title
NEUROCOMPUTING
Volume
267
Start Page
169
End Page
181
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/81206
DOI
10.1016/j.neucom.2017.06.009
ISSN
0925-2312
Abstract
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. (C) 2017 Elsevier B.V. All rights reserved.
Files in This Item
There are no files associated with this item.
Appears in
Collections
Graduate School > Department of Artificial Intelligence > 1. Journal Articles

qrcode

Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.

Related Researcher

Researcher Lee, Seong Whan photo

Lee, Seong Whan
인공지능학과
Read more

Altmetrics

Total Views & Downloads

BROWSE