Student Name : Saif SamaanStudent Number :42083850Supervisor: Manolya Kavakli

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Abstract Introduction Literature Review Experiments and Analysis Experiments Survey and Results Conclusion

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A computer contains three main parts, input interfaces, processing devices and output interfaces.

Input and output interfaces called, Human Computer Interfaces (HCI), these interfaces provides the communication environment between human and computers.

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This project aims to explore human hand-gesture classification from a designer point of view, to support a discovery project sponsored by the Australian Research Council.

The discovery project examines a novel environment in which a designer can define the contour of a sketch by controlling a pointer using a pair of data gloves and can interact with the design product in 3D space.

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I provide an analysis study for current and

previous hand-gesture recognition systems,

also I experiment the gesture design

process with twenty volunteers, and I

defined a set of suggested gestures,

techniques and possible future challenges.

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Abstract Introduction Literature Review Experiments and Analysis Experiments Survey and Results Conclusion

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This section presents the background and a general description for the problem and the aim of this project.◦ Background

Human-computer interfaces (HCI) logic have developed through different stages using different tools, traditional tools like keyboards for text input, mice,2D and 3D graphical interfaces and sophisticated 3D virtual environment (VE) systems.

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◦Problem Description Most human-machine interfaces based

on joysticks, keyboards, and keypads,

but few such interfaces use gestures.

Interaction based on hand gestures

commonly uses two types of interface,

gloved-based and vision-based .

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◦ Vision-based interfaces require powerful image processing algorithms to segment the hand from stationary background and lighting conditions that enhance gesture classification accuracy.

◦ A glove- based system requires the user to be connected to the computer.

Even wireless systems currently offered in the market require the user to wear a glove. Furthermore, accurate devices are expensive and hard to calibrate.

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◦The Aim of this work

The main aim of this report is to explore

human computer interaction and

gesture recognition, in order to support

the design process.

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Abstract Introduction Literature Review Experiments and Analysis Experiments Survey and Results Conclusion

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1-Video Capture(Vision-based Technology)

◦Using one camera or more to record images of

human hand Gestures.

Infrared-camera Based System

Mono-camera Based Gesture Recognition

System

Multi-camera Based Gesture Recognition

System

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13

Infrared camera

Mono-camera Multi-camera

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2-Image Segmentation

◦Threshold-Based Segmentation

◦ Active Contour Models

◦ Split and Merge

◦ Boundary Based Segmentation

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3-Image Processing

The computer detects images

produced from original hand image

but usually the quality of the detected

images comes along with a level of

noise.

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Image capture

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//Code of capturing image sequence

• int width=320;//Define the image resolution ratio

• int height=240;

• IplImage *pRgb=cvCreateImage(cvSize(width,height),

IPL_DEPTH_8U, 3);

videoInput video;//Create capturing object

video.setupDevice(0, width, height);//Configure device

while(1)

{

if(video.isFrameNew(0) 

{ 

video.getPixels(0,(unsigned char *)pRgb->imageData, false, true);//Capture one frame 

char c=cvWaitKey(1);

if(c==27) break;//Press ESC to exit

cvShowImage(“Video”, pRgb);//Show display window

}

 

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18

Cyber-glove (http://www.immersion.com/ )

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Vision-Based and Sensors-Based

19

“Rise of the Planet of the Apes (2011)”

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4-Gesture Classification

David McNeill specifies four types of

gestures, which are part of human

communication, they are, iconics,

metaphorics , beats and deictics.

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Abstract Introduction Literature Review Experiments and Analysis Experiments Survey and Results Conclusion

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Twenty volunteers helped me in my experiments.

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J. Liu and M. Kavakli, “Temporal Relation between Speech and Co-verbal Iconic Gestures in Multimodal Interface Design,”

◦ Differences and similarities in human gestures

◦ Single Line description◦ 13/20 volunteers:

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◦ Differences and similarities in human gestures

◦ Single Line description◦ 1/20 volunteer:

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◦ Differences and similarities in human gestures

◦ Single Line description◦ 6/20 volunteer:

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Two Parallels Lines description.

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Twenty volunteers helped me in my experiments.

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Curve description.

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Circle description.

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Start and end point.

First hand

Second hand

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Critical region problem.

First hand

Second hand

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Curve description:

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Abstract Introduction Literature Review Experiments and Analysis Experiments Survey and Results Conclusion

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Left Public for future study

https://docs.google.com/spreadsheet/viewform?formkey=dFVOcklIaXV1b3c0d25BaHhpMVp5Q3c6MQ

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5-Do you agree that gesture-recognition system replace the keyboard and mouse?

80% Not now

17% Disagree

3% Agree

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9- If you have to chose only one input device with

gesture recognition system, which one you will

select?

80% Touch screen

15% Mouse

5% Keyboard

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Abstract Introduction Literature Review Experiments and Analysis Experiments Survey and Results Conclusion

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The project is outlining a hand gesture recognition system that designed to be capable to recognize the hand gestures in real time, this will be in a picture of examining environment in which a designer can sketch by controlling a pointer using a pair of cyber gloves and can interact with the design product in 3D space.

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