1.
A Hand Gesture Representation
System
Based on Machine Learning
Presented by

2.
Outline
 Introduction
 Objective
 Significance
 References

3.
Introduction
 In this project, we will learn how to
create a Hand Gesture based
Presentation system. Computers should
communicate with people with body
language.
 Hand gesture recognition becomes
important
 Interactive human-machine interface and
virtual environment

4.
Introduction
 And to make it more usable we will add
an erasing gesture as well.
 We will be able to move the slides back
and forth along with a pointer and
drawing capabilities.

5.
Objective
 To convert a hand motion or gesture into mouse
input that will be allocated to a certain screen
position
 Set the camera to capture photographs indefinitely,
which will subsequently be analyzed using various
image processing methods.
 Detection of Hand Gesture Regions
 Aim to fix on the valid frames and locate the hand
region from the rest of the image.

6.
Pre-processing of
Hand Gesture Recognition
 Detection of Hand Gesture Regions
 Aim to fix on the valid frames and
locate the hand region from the rest of
the image.
 Low time consuming  fast processing
rate  real time speed

7.
Significance
 This project has been formulated an evaluative observe on a
few gesture detection systems, their mode of operation, system
description and some outcomes and so on Aim to fix on the
valid frames and locate the hand region from the rest of the
image.
 A few strategies have to be created since precision and
efficiency play a crucial part in making the application as helpful
as a real physical device.
 Following the deployment of an application, physical devices are
significantly replaced, i.e., no need for any actual mouse or
keyboard. Every actual mouse or keyboard action employs this
motion detection gesture (Hand gesture recognition).

8.
REFERENCES
•Konstantinos G. Derpanis. “A Review of VisionBased
Hand Gestures” (2004). https://www.computervision.zone/
• [2] Sushmita Mitra, and Tinku Acharya, “Gesture
Recognition: A Survey”, IEEE Transactions on Systems,
Man and Cybernetics–Part C: Applications and Reviews,
37(3) (2007).
• [3] T. S. Hunang and V. I. Pavloic, “Hand Gesture
Modeling, Analysis, and Synthesis,” Proc. of Int. Workshop
on Automatic Face and Gesture Recognition, Zurich, (1995),
73-79.
• [4] Dnyanada R Jadhav, L. M. R. J Lobo, Navigation of
PowerPoint Using Hand Gestures, International Journal of
Science and Research (IJSR) 2015.