DocumentCode
2100631
Title
Human motion segmentation and object recognition using fuzzy rules
Author
Hunter, J.E.
Author_Institution
Center for Intelligent Syst., Vanderbilt Univ., Nashville, TN, USA
fYear
2005
fDate
13-15 Aug. 2005
Firstpage
210
Lastpage
216
Abstract
Our goal is to develop an object recognition and motion tracking system to assist in the analysis of data for a project in the psychology and human development department. Fuzzy membership rules provide a viable solution for creating this system. We describe our development of the feature vector, rule extraction, and image segmentation. The usefulness of the system is demonstrated via an analysis of videos of human action collected as part of an on-going collaboration with researchers in the Vanderbilt Psychology and Human Development department. Results are given to show the current progress, and future goals are presented.
Keywords
image motion analysis; knowledge based systems; learning (artificial intelligence); object recognition; robot vision; social sciences computing; feature vector; fuzzy membership rules; fuzzy rules; human motion segmentation; image segmentation; motion tracking system; object recognition; rule extraction; Computer vision; Data analysis; Fuzzy systems; Humans; Image motion analysis; Motion analysis; Motion segmentation; Object recognition; Psychology; Tracking;
fLanguage
English
Publisher
ieee
Conference_Titel
Robot and Human Interactive Communication, 2005. ROMAN 2005. IEEE International Workshop on
Print_ISBN
0-7803-9274-4
Type
conf
DOI
10.1109/ROMAN.2005.1513781
Filename
1513781
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