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