Abstract

Virtual museum is a place where users can explore museum collection freely. In this study, we are discussing the 3D interactions presented in a virtual museum application using hand-sensing sensor named Leap Motion. In making 3D interaction, some hand gestures are needed to functions any interact in virtual world. To prevent miss-occurring in 3D interaction, it is necessary to do a hand pattern classification to improve accuracy and make it more precision so as not to reduce the quality of immersion in the virtual world. The classification method used in this study is K-Nearest Neighbor (KNN) classification methods. KNN is a method that is quite popular and simple. The first step is data acquisition processing that is used as training data using Leap Motion Controller which takes vector value data (x, y, z) from each fingertip. Then the data normalization process is carried out to facilitate the next process which is feature extraction process. Features are being extracted including angle value between fingers, angle value between fingertips, angle between fingertips and palms, distance vector between fingertips and palms, and elevation value between fingertips and palms. After that, extracted data are being trained and classified using K-Nearest Neighbor (KNN).

Original languageEnglish
Title of host publication2019 International Conference on Computer Engineering, Network, and Intelligent Multimedia, CENIM 2019 - Proceeding
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728129655
DOIs
Publication statusPublished - Nov 2019
Event2nd International Conference on Computer Engineering, Network, and Intelligent Multimedia, CENIM 2019 - Surabaya, Indonesia
Duration: 19 Nov 201920 Nov 2019

Publication series

Name2019 International Conference on Computer Engineering, Network, and Intelligent Multimedia, CENIM 2019 - Proceeding
Volume2019-November

Conference

Conference2nd International Conference on Computer Engineering, Network, and Intelligent Multimedia, CENIM 2019
Country/TerritoryIndonesia
CitySurabaya
Period19/11/1920/11/19

Keywords

  • KNN
  • data classification
  • leap motion
  • preprocessing
  • virtual museum

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