NDLI: Multi-rate recognition of human gestures by concurrent frame rate control

Content Provider	IEEE Xplore Digital Library
Author	Kirishima, T. Manabe, Y. Sato, K. Chihara, K.
Copyright Year	2008
Description	Author affiliation: Grad. Sch. of Eng. Sci., Osaka Univ., Osaka (Sato, K.) \|\| Grad. Sch. of Inf. Sci., Nara Inst. of Sci. & Technol., Ikoma (Kirishima, T.; Manabe, Y.; Chihara, K.)
Abstract	In order to sufficiently represent and recognize human gestures, one needs, in the first place, to know at what frame rate a gesture should be sampled. To investigate the temporal-domain problems on gesture recognition, a framework is proposed that recognizes arbitrary gestures at multiple frame rate by running recognition processes in parallel. In our system, each recognition process runs on-line and in real-time by controlling the frame rate autonomously. As a benchmark image database, we use the ViHASi (Virtual Human Action Silhouette) database which is publicly available. We created an original image database that contains 18 kinds of sporting and stretching gestures, both are to evaluate the recognition performance under different frame rate conditions. By examining the recognition rates of each gesture at each frame rate, we found gestures that exhibit frame rate dependency and the gestures that do not. We experimentally demonstrate that the dependency is largely determined by the distinctiveness among target gestures.
Starting Page	1
Ending Page	6
File Size	324453
Page Count	6
File Format	PDF
ISBN	9781424437801
DOI	10.1109/IVCNZ.2008.4762095
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-11-26
Publisher Place	New Zealand
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Pervasive computing Real time systems Image recognition Protocols Humans concurrent frame rate control Control systems Multi-rate gesture recognition Information science Image databases Convolution Speech recognition distributed image processing
Content Type	Text
Resource Type	Article

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