Smartphone sensors selection using decision tree and KNN to detect head movements in Virtual Reality Application

PubDate: December 2017

Teams: Bina Nusantara University

Writers: Maria Seraphina Astriani ; Gede Putra Kusuma ; Yaya Heryadi ; Edi Abdurachman

PDF: Smartphone sensors selection using decision tree and KNN to detect head movements in Virtual Reality Application

Abstract

There are a lot of Virtual Reality applications on smartphone because nowadays smartphones are equipped with varies sensors. These sensors can be used to detect head movements in order to navigate the virtual world. Selecting the combinations of smartphone sensors that are suitable for detecting head movements is still in the grey area because there is no guidance for selecting the sensors and different researchers use different sets of sensors in smartphone. If the selection of relevant sensors has not been chosen wisely, the detection accuracy will not optimal. Detection Knowledge Algorithm with the combination of machine learning are the perfect combination for detecting head movement. Decision Tree and KNN methods are chosen because these methods are able to run on smartphone. Based on the experiment, accelerometer, gyroscope, and magnetometer combination has the highest accuracy result compared with other and suitable to be used in virtual reality application.