A Training Gesture-Based-Scroll Visual Artificial Intelligence And Measuring Its Effectiveness Using Hidden-Markov Modeling Methods
| Autor: | Arif Wibisono |
|---|---|
| Jazyk: | English<br />Indonesian |
| Rok vydání: | 2020 |
| Předmět: | |
| Zdroj: | Journal of Information Systems and Informatics, Vol 2, Iss 1, Pp 163-168 (2020) |
| Druh dokumentu: | article |
| ISSN: | 2656-5935 2656-4882 |
| DOI: | 10.33557/journalisi.v2i1.58 |
| Popis: | 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 3 fps / 15 frames and stop 3 fps / 9 frames, the result is that the most effective hand gesture object training movement is stopped 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. |
| Databáze: | Directory of Open Access Journals |
| Externí odkaz: |
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