NDLI: An Apriori-like algorithm for automatic extraction of the common action characteristics

Content Provider	IEEE Xplore Digital Library
Author	Tran Thang Thanh Fan Chen Kotani, K. Bac Le
Copyright Year	2013
Description	Author affiliation: Sch. of Inf. Sci., Japan Adv. Inst. of Sci. & Technol., Nomi, Japan (Tran Thang Thanh; Fan Chen; Kotani, K.) \|\| Fac. of Inf. Technol., Univ. of Sci., Ho Chi Minh City, Vietnam (Bac Le)
Abstract	With the development of the technology like 3D specialized markers, we could capture the moving signals from marker joints and create a huge set of 3D action MoCap data. The more we understand the human action, the better we could apply it to applications like security, analysis of sports, game etc. In order to find the semantically representative features of human actions, we extract the sets of action characteristics which appear frequently in the database. We then propose an Apriori-like algorithm to automatically extract the common sets shared by different action classes. The extracted representative action characteristics are defined in the semantic level, so that it better describes the intrinsic differences between various actions. In our experiments, we show that the knowledge extracted by this method achieves high accuracy of over 80% in recognizing actions on both training and testing data.
Starting Page	1
Ending Page	6
File Size	509650
Page Count	6
File Format	PDF
e-ISBN	9781479902903
DOI	10.1109/VCIP.2013.6706394
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-11-17
Publisher Place	Malaysia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Three-dimensional displays Databases Action Characteristics Semantics Relational Features Feature extraction Data Mining Neck Semantic-based Data mining Joints 3D Mocap Data
Content Type	Text
Resource Type	Article

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