Programski vmesnik za dinamično razpoznavanje gest z zapestnico Myo

diplomsko delo

Blaž Sitar (Author), Aleš Holobar (Mentor)

Abstract

V diplomskem delu je predstavljen programski vmesnik, ki bo znal razpoznavati geste roke pri interakciji človek – stroj. Tehnologija prehaja v obdobje, kjer se uveljavljajo novi načini interakcije človeka s strojem in nam omogoča lažje upravljanje in učenje strojev samih. Čeprav še vedno na področju interakcije s stroji prevladujeta miška in tipkovnica, se v ospredje prebijajo tudi druge naprave, ki omogočajo enake ali celo boljše interakcije človek – stroj. Eden izmed takšnih proizvodov je tudi zapestnica Myo, ki je v diplomskem delu uporabljena za zajemanje in analizo poljubnih uporabnikovih gest roke. Napisan je programski vmesnik, ki je zmožen učenja in razpoznavanja gest, ter testirano, kako dobro se obnese pri razpoznavanju različnih gest. Meritve nakazujejo, da je programski vmesnik pravilno razpoznal večino naučenih gest, iz česar je možno sklepati, da je zmožen prepoznati dinamično naučene geste.

Keywords

programski vmesniki;interakcija človek-stroj;razpoznavanje gest;zapestnica Myo;strojno učenje;diplomske naloge;

Data

Language:	Slovenian
Year of publishing:	2016
Typology:	2.11 - Undergraduate Thesis
Organization:	UM FERI - Faculty of Electrical Engineering and Computer Science
Publisher:	B. Sitar
UDC:	004.5:004.8(043.2)
COBISS:	20184086
Views:	1115
Downloads:	126
Average score:	0 (0 votes)
Metadata:

Other data

Secondary language:	English
Secondary title:	PROGRAM INTERFACE FOR DYNAMIC GESTURE RECOGNITION WITH MYO ARMBAND
Secondary abstract:	We describe a program interface for dynamic gesture recognition in human-computer interaction. Technology is forcing new ways of human-machine interaction which enables faster learning and more complex controlling of machines, such as computers. Mouse and keyboard are still dominant devices for interaction with computers, but other devices are rushing ahead. One of these devices is Myo armband, which has been used in our work to acquire and analyze the hand gestures. We wrote a program interface, which learns arbitrary gestures and systematically analyses differences between different gestures in order to illuminate the accuracy of their automatic classification and discrimination. We tested the interface on 5 gestures and demonstrated that our program recognized most of learnt gestures and we can say it’s capable of recognizing dynamically learnt gestures
Secondary keywords:	program interface;human-machine interaction;Myo armband;gesture recognition;machine learning;
URN:	URN:SI:UM:
Type (COBISS):	Bachelor thesis/paper
Thesis comment:	Univ. v Mariboru, Fak. za elektrotehniko, računalništvo in informatiko, Računalništvo in informacijske tehnologije
Pages:	V, 37 str.
ID:	9161825