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Sistem Gesture Accelerometer dengan Metode Fast Dynamic Time Warping (FastDTW)

*Sam Farisa Chaerul Haviana  -  Universitas Islam Sultan Agung, Indonesia

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Abstract

In the modern environment, the interaction between humans and computers require a more natural form of interaction. Therefore, it is important to be able to build a system that can meet these demands, such as by building a hand gesture recognition system or gesture to create a more natural form of interaction. This study aims to design a smartphone’s accelerometer gesture system as human computer interaction interfaces using FastDTW (Fast Dynamic Time Warping).The result of this study is form of gesture interaction which implemented in a system that can make the process of recognition of the human hand movements based on a smartphone accelerometer which generates a command to run the media player application functions as a case study. FastDTW as the development of Dynamic Time Warping method (DTW) is able to compute faster than DTW and have an accuracy approaching DTW. From the test results, FastDTW show a fairly high degree of accuracy reached 86% and showed a better computing speed compared to DTW

 

 

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Keywords: Human and Computer Interaction, Accelerometer-based gesture, FastDTW, Media player application function

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Section: Research Articles
Language : EN
  1. Akl, A., 2010. A Novel Accelerometer-based Gesture Recognition System, Master Thesis. Toronto: Master of Applied Science Department of Electrical and Computer Engineering University of Toronto
  2. Kela, J., 2006. Accelerometer-based gesture control for a design environment. Pers Ubiquit Comput, 285–299
  3. Liu, J., Wang, Z., Zhong, L., Wickramasuriya, J., and Vasudevan, V., 2008. uWave: Accelerometer-based Personalized Gesture Recognition. Houston: Rice University and Motorola Labs
  4. Salvador, S., and Chan, P., 2007. FastDTW: Toward Accurate Dynamic Time Warping in Linear Time and Space. Prcoeedings of the 10th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining Workshop on Mining Temporal and Sequential Data ,hal. 70–80, Melbourne: Dept. of Computer Sciences Florida Institute of Technology
  5. Weiser, M., Gold, R., and Brown, R. J., 1999. The origins of ubiquitous computing research at PARC in the late 1980s. IBM SYSTEMS JOURNAL, VOL 38, NO 4, 693-696
  6. Wu, J., Pan, G., Zhang, D., Qi, G., and Li, S., 2009. Gesture Recognition with a 3-D Accelerometer. UIC LNCS 5585, Springer-Verlag Berlin Heidelberg, 25-38

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