DocumentCode :
3468939
Title :
Human Body-Parts Tracking for Fine-Grained Behavior Classification
Author :
Ukita, Norimichi ; Nakazawa, Atsushi
fYear :
2013
fDate :
2-8 Dec. 2013
Firstpage :
777
Lastpage :
778
Abstract :
This paper discusses the usefulness of human body-parts tracking for acquiring subtle cues in social interactions. While many kinds of body-parts tracking algorithms have been proposed, we focus on particle filtering-based tracking using prior models, which have several advantages for researches on social interactions. As a first step for extracting subtle cues from videos of social interaction behaviors, the advantages, disadvantages, and prospective properties of the body-parts tracking using prior models are summarized with actual results.
Keywords :
behavioural sciences computing; feature extraction; image classification; object tracking; particle filtering (numerical methods); video signal processing; fine-grained behavior classification; human body-part tracking; particle filtering-based tracking; prior models; prospective properties; social interaction behavior videos; social interactions; subtle cues; Autism; Biological system modeling; Probabilistic logic; Robustness; Tracking; Trajectory; Videos; body-parts tracking; social interactions;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Vision Workshops (ICCVW), 2013 IEEE International Conference on
Conference_Location :
Sydney, NSW
Type :
conf
DOI :
10.1109/ICCVW.2013.106
Filename :
6755975
Link To Document :
بازگشت