@inproceedings{a480264e5db44721bbb3c3cd73e1645f,
title = "Modeling spatial relations of human body parts for indexing and retrieving close character interactions",
abstract = "Retrieving pre-captured human motion for analyzing and synthesizing virtual character movement have been widely used in Virtual Reality (VR) and interactive computer graphics applications. In this paper, we propose a new human pose representation, called Spatial Relations of Human Body Parts (SRBP), to represent spatial relations between body parts of the subject(s), which intuitively describes how much the body parts are interacting with each other. Since SRBP is computed from the local structure (i.e. multiple body parts in proximity) of the pose instead of the information from individual or pairwise joints as in previous approaches, the new representation is robust to minor variations of individual joint location. Experimental results show that SRBP outperforms the existing skeleton-based motion retrieval and classification approaches on benchmark databases.",
keywords = "Close interaction, Human motion, Motion classification, Motion retrieval, Spatial relations",
author = "HO, {Shu Lim} and CHAN, {Chun Pong} and CHEUNG, {Yiu Ming} and YUEN, {Pong Chi}",
note = "Funding Information: This work was supported in part by Hong Kong RGC (GRF210813) and the National Natural Science Foundation of China (61302176).; 21st ACM Symposium on Virtual Reality Software and Technology, VRST 2015 ; Conference date: 13-11-2015 Through 15-11-2015",
year = "2015",
month = nov,
day = "13",
doi = "10.1145/2821592.2821617",
language = "English",
series = "Proceedings of the ACM Symposium on Virtual Reality Software and Technology, VRST",
publisher = "Association for Computing Machinery (ACM)",
pages = "187--190",
editor = "Spencer, {Stephen N.}",
booktitle = "Proceedings - VRST 2015",
address = "United States",
}