Gesture tank: a gesture detection water vessel for foot movements

K S Lasith Gunawardena,Masahito Hirakawa

doi:10.4038/icter.v8i2.7163

Abstract

Computers have become ubiquitous and integrated into our day-to-day activities. Researchers have been exploring mechanisms for interacting with computers using natural means in natural environments. Water interaction is a perfect example. This paper presents our attempt to use foot gestures performed in water as an interaction mechanism. It is an extension of our previous study for detecting objects in a water vessel. An experiment was performed to determine which foot-based gestures are suitable for implementation, and we proceeded to recognize a selected set of gestures using machine-learning techniques. We present our findings regarding which algorithms provide the best recognition rates.

Highlights

The need to use a keyboard and mouse limits our interactions with computers
Plantar flexion: rotation of the ankle that increases the angle between the shin and foot
The support vector machines (SVM) classified Gestures 3 and 6 with 100% accuracy, with the lowest performance for Gesture 7 at 89%

Summary

Introduction

Novel interaction techniques have become necessary because of the need to be connected on a continuous basis while engaging in day-to-day activities. This is true because computing devices are no longer seen as data processing devices but as gateways to activities such as knowledge acquisition and entertainment. Many researchers have attempted to develop schemes to detect human gestures, regarding vision-based research using one or more cameras as sensors. In the past decade, there has been an increased focus on detecting gestures using non-vision-based sensors or hybrid devices using a combination of cameras and other sensors. The typical limits for inversion and eversion are 20°–30° and 5°–15° [21], respectively. The ranges of motion for dorsiflexion and plantar flexion are 10°–20° and 40°–55°, respectively [22]

Objectives

Methods

Results

Conclusion