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Improving gesture recognition perfor...

Hanson, Danny Allen.

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Improving gesture recognition performance using the dynamic space-time warp algorithm.

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Improving gesture recognition performance using the dynamic space-time warp algorithm./
作者:	Hanson, Danny Allen.
面頁冊數:	72 p.
附註:	Source: Masters Abstracts International, Volume: 52-01.
Contained By:	Masters Abstracts International52-01(E).
標題:	Computer Science. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1541286
ISBN:	9781303236976

Improving gesture recognition performance using the dynamic space-time warp algorithm.
Hanson, Danny Allen.

Improving gesture recognition performance using the dynamic space-time warp algorithm. - 72 p.

Source: Masters Abstracts International, Volume: 52-01.

Thesis (M.S.)--The University of Texas at Arlington, 2013.

The DSTW algorithm was originally used as the fundamental algorithm for a gesture recognition software. When the need arose for implementing gesture recognition on-board a robotic vehicle, the original recognition software needed to undergo several changes in order to meet the requirements of the target platform. The original software was written in Matlab and had to be ported into a native language in order to operate on the new platform. To support experiments needed to select a distance and tau function, the new code needed to be designed to support dynamic binding of distance and transition (tau) functions. The software needed to handle over 140 experiments to determine the appropriate distance and tau functions. A new classifier based on the A* algorithm was proposed and implemented to further reduce runtime performance, and a new tau function based on template matching between the various candidates provided by the detector was proposed and implemented. This work covers the results of theses efforts in Improving Gesture Recognition Performance using the Dynamic Space-Time Warp Algorithm.

ISBN: 9781303236976Subjects--Topical Terms:

626642
Computer Science.

Improving gesture recognition performance using the dynamic space-time warp algorithm.
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