TELEKINESYS Group Members: Mir Murtaza SM Rasikh Mukarram Shiraz Sohail

INTRODUCTION REAL WORLD PROBLEM Projection of screen is widely used in presentations and teaching at IBA. The presenter keeps himself/herself in the proximity of the computer system to control it. Lacks the naturalness of the interaction. Our proposed solution: Control the mouse functions with hand gestures IBA CED

SOLUTION Using camera to allow the same kind of user input as touch-screens do, but with a lower price and a larger screen.

OUR APPROACH CAMERA-PROJECTOR CONFIGURATION CONTROLS THE MOUSE. CAMERA HAND + GESTURES’ DETECTION HAND DETECTION AND GESTURE DETECTION: USING LED LIGHTS HAND +GESTURES DETECTION MOUSE FUNCTIONS

IMPLEMENTATION THE SYSTEM DESIGN INPUT INTERFACE OUTPUT

METHODOLOGY Input includes: 1.Valid Region Detection 2.Hand Detection Using LED Lights 3.Gesture Detection Interface  communicate between the recognition part and the OS. Input data  Interface Interface  performs the action

Valid Region Detection Valid region is the projected screen. Rectangular Screen property. openCV function cvfindcountours. Valid and Invalid region The alignment of web camera User confirmation of screen

Hand Detection Using LED Lights LED lights  locates position of the hand. Three LED lights sufficient. Noise filtering can be done in two ways: 1.Set the level of threshold to filter all the light of less intensity. 2.Cover the camera lens with a black film negative.

Gesture Detection A maximum of three light sources can be detected: 1.The light that is closest to the track point is the first light F; 2.The second light at the left hand side of F is L; 3.The third light at the right hand side of F is R.

Gesture Detection By LED Poistions forefinger LED light  point F When light L appears on the left hand side of light F, then left click is executed. When light R appears on the right hand side of light F, then right click is executed. If three lights appear for a second, then the function of scrolling is executed. Valid and invalid gestures.

Software Requirements OpenCV – computer vision library. C++ – working with OpenCV to analyze the hand shape and gesture. Bloodshed Dev-C++ – acts as complier Matlab – for machine learning.

Hardware Requirements 1.Projector Installed in every class of IBA. 2.Webcam Easily available and affordable. Laptop’s camera can also be used. 3.LED Lights: Three 1V LED lights + 9V battery + Gloves

End deliverables A webcam with a particular resolution with its lens covered with a black film negative to filter all the noise and light entering into the classroom. A Hand Glove with LED system integrated. This covers three 1Volt LED lights connected in parallel with a 9 volt battery. The battery lifetime is around 20 days if kept switched on continuously. The system also consists of 1pos On-Off switch which is used for simultaneous control of all 3 LED lights.

Related Work Sit Chu Wah, Sin Kwok San and Luk Tsan Kwong Prof. Brian Kan-Wing MAK Attila Licsár1, Tamás Szirányi1,2

Future Scope Projects’ completion is base for uncovered hand and gesture recognition system. The hand gestures complexity Our research and work plan for future.

References Sit Chu Wah, Sin Kwok San and Luk Tsan Kwong Prof. Brian Kan-Wing MAK Attila Licsár1, Tamás Szirányi1,2 Antonis A. Argyros and Manolis I.A. Lourakis