A Training Gesture-Based-Scroll Visual Artificial Intelligence And Measuring Its Effectiveness Using Hidden-Markov Modeling Methods
2020 ◽
Vol 2
(1)
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pp. 163-168
Keyword(s):
In this article I discuss the method of hand gesture recognition as a visual motion detection based on artificial intelligence by training three main movements namely, scrolling up, scrolling down and stopping based on capturing the front camera image capture speed of 3 fps and measuring its efficiency against the control movements that performed using Hidden-Markov Modeling (HMM) with each catch object scroll up 3 fps / 15 frames scroll down scroll down 3 fps / 15 frames and stop 3 fps / 9 frames, the result is that the most effective hand gesture object training movement is stop gesture with 3 fps / 9 frames because the object's movement is able to be recognized by the system only in the 3rd second image capture frame.
2021 ◽
pp. 001872082110328
2009 ◽
Vol 13
(6)
◽
pp. 417-419
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Keyword(s):
2012 ◽
Vol 2012
(1)
◽
Keyword(s):
2011 ◽
pp. 411-463
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