Deteksi Gestur Lengan Dinamis pada Lingkungan Virtual Tiga Dimensi Koleksi Warisan Budaya

  • Adri Gabriel Sooai Institut Teknologi Sepuluh Nopembe
  • Atyanta. N. Rumaksari Universitas Kristen Satya Wacana
  • Khamid Khamid Institut Teknologi Sepuluh Nopember
  • Nurul Zainal Fanani Institut Teknologi Sepuluh Nopember
  • Surya Sumpeno Institut Teknologi Sepuluh Nopember
  • Mauridhi Hery Purnomo Institut Teknologi Sepuluh Nopember
Keywords: Gaussian Mixture Model, Gestur Lengan Dinamis, k-NN, Koleksi Warisan Budaya, Virtual Reality

Abstract

Virtual reality technology can be used to support museum exhibitions. Implementation could be in various platforms. There are many implementation options, for example in smartphones, tablet, and desktop computers. Most objects of museum collections are very fragile. Minimizing the direct touch on a collection object is one of the benefits of this technology. This study aims to prepare gestures suitable for the exploration of virtual objects of cultural heritage collection. Five sets of gestures have been prepared, namely lifting, picking, holding, sweeping from both directions, left and right. Dynamic arm gestures are recorded using the forearm sensor. The recorded data contains coordinates of gestures in form of x, y, z, raw, pitch, and yaw. Gaussian mixture models are used in selecting features to produce good accuracy in the classification process.Two functions are used, namely probability density function and cumulative distribution function for the feature selection process. In this study, two experiments were used to train the gesture model. The accuracy of the two experiments is shown in the form of a confusion matrix. Each of the confusion matrices show excellent results of 99.8% for SVM and k-NN. Furthermore, modeling results are tested using new data. The testing shows 89.25% result for SVM classifier and 90.09% for k-NN. Four other dynamic arm gestures have a very satisfactory rate of 100% for the two classifiers. The five gestures can be used in the development of virtual reality applications.

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Published
2018-11-22
How to Cite
Adri Gabriel Sooai, Atyanta. N. Rumaksari, Khamid Khamid, Nurul Zainal Fanani, Surya Sumpeno, & Mauridhi Hery Purnomo. (2018). Deteksi Gestur Lengan Dinamis pada Lingkungan Virtual Tiga Dimensi Koleksi Warisan Budaya. Jurnal Nasional Teknik Elektro Dan Teknologi Informasi, 7(4), 397-403. Retrieved from https://dev.journal.ugm.ac.id/v3/JNTETI/article/view/2633
Section
Articles