Gesture Recognition System
Speaker ：Bo – Hung Chen
Adviser ：Dr. Shih – Chung Chen
Outline
Introduction
 Paper Review
 Material
 Methods
 Results
 Conclusion
 Future Works
 Reference

Introduction

What is Gesture Recognition?


It is the process by which the gestures made by the
user are recognized by the receiver
Motivation
◦ Ranging from sign language through medical
rehabilitation to virtual reality
Introduction

Wide-ranging applications such as the
following：
◦ Developing aids for the hearing impaired
◦ Enabling very young children to interact with
computers
◦ Designing techniques for forensic identification
◦ Recognizing sign language
◦ Medically monitoring patients’ emotional states or
stress levels
Reference ： Gesture Recognition: A Survey , Sushmita Mitra, Senior Member, IEEE, and Tinku Acharya, Senior Member, IEEE
Introduction

Wide-ranging applications such as the
following：
◦ Lie detection
◦ Navigating and/or manipulating in virtual
environments
◦ Communicating in video conferencing
◦ Distance learning/tele-teaching assistance
◦ Monitoring automobile drivers’
alertness/drowsiness levels, etc
Reference ： Gesture Recognition: A Survey , Sushmita Mitra, Senior Member, IEEE, and Tinku Acharya, Senior Member, IEEE
Introduction

Commonly type：
◦ Morphological
◦ Moving path tracking
Paper Review
Alphanumeric Shape Recognition of Fingertip Writing
Trajectory
Ruei-Tang Lin , Ming-Fang Wu
Kun Shan University , Department of Electrical Engineering, 2010
Paper Review
Paper Review
Sign Language for Numbers Recognition to Speech Translation System
Student : Rubie Fernando Vinas, Advisor : Dr. Shih-Chung Chen
Southern Taiwan University
Department of Electrical Engineering
Master’s Thesis
AND
Material
LabVIEW2010
Use USB camera
PC
Methods

Image processing

Skin Color Swatches
Fill Hole
Remove
Particle
Dilate
Thin
Methods

Tags
Methods

Tags
Methods

Recognition rules：ROI
Extract
Extract
½ Long
ROI： Range Of Interesting
Methods

Recognition Rules：ROI
ROI： Range Of Interesting
Methods

Mouse Control
Methods

Mouse Move
Results

Recognition Results
Results

Problem
Huge “Particle”(Item, background, etc)
will not be removed
In somehow ,Webcam is just not good
enough for recognition(too much limited)
Conclusion
Gesture Recognition System can be use to
control mouse or else human computer
interface
 Users must be trained to get used to the
camera(Distance, Angle, etc)
 USB webcam is not only the cheapest one,
but also the most limitations one

Future Works
Try to use another camera(But not too
expensive)
 Fix skin color problem
 Try to use new tag rule

Reference

[1]張光寒, ”3D 台灣手語辨識系統” , 南台科技大學電機工程研究所, 96年

[2]陳為尹, ”資料手套與影像辨識之手勢控制應用” , 南台科技大學生物醫學工程研究所, 99年

[3]洪兆欣, ”以軌跡辨識為基礎之手勢辨識系統” ,國立中央大學資訊工程研究所, 95年

[4]吳明芳、林瑞堂， ”指尖手寫軌跡的字形辨識” ，崑山科技大學電機工程系碩士論文，2009年。

[5] Yunli Lee, Seungki Min, HwangKyu Yang, and Keechul Jung , ” Motion Sensitive Glove-based Korean
Fingerspelling Tutor” HCI Lab, School of Media, College of Information Technology, Soongsil
University,2007

[6] Bui, T.D.; Nguyen, L.T. ” Recognizing Postures in Vietnamese Sign Language With MEMS Accelerometers”
Sensors Journal, IEEE Volume 7, Issue 5, May 2007

[7] Rubie Fernando Vinas, “Sign Language for Numbers Recognition to Speech Translation System ”, 南台科技大學電機
工程研究所

[8] Stan Z. Li Anil K. Jain, “Handbook of Face Recognition Second Edition” , Springer-Verlag London Limited 2011
Thanks for your attention!