Innovative 3D Gesture Recognition for Educational Gaming
Study of 3D Gesture-Recognition
Based Animation Game
Ishita Shah, Niyati Gosalia, Priya Jain,
Abhijit R. Joshi, Neha Katre
(D.J. Sanghvi College of Engineering)
Sameer Sahasrabuddhe
(TISS, Mumbai)
Scope & Purpose
•
Benefits of E-learning :
Interactivity
Anytime, Anywhere
60% faster learning curve (Facts, Figures and Forces Behind E-
Learning )
Bridges gap between student and instructor
•
Benefits of Gesture Based Interactive games :
Physical movement during gameplay v/s sedentary gameplay
2
Developed by - Adeet Shah, Mohini Thakkar, Varun Thakkar
(D. J. Sanghvi College of Enginnering)
Mathmazing Version 1.0
3
Drawbacks of Existing System
•
Dependency on Kinect
•
Requires NITE, PrimeSense, OpenNi libraries
•
Lack of Devnagari support
•
Lack of Challenge
•
No Instructional tutorial
4
Mathmazing 2.0
Features :
•
Single player
•
Web camera for gesture capture
•
Multi level
•
Blender Game Engine
5
Workflow of Mathmazing 1.0
6
Gestures
detected by
KINECT
FAAST
Converts gestures
into key press events
Key press event
passed to .exe of
the game
Workflow of Mathmazing 2.0
7
Gestures
detected by
Camera
OPENCV
Detects and Converts
gestures into key press
events
Key press event
passed to .exe of
the game
Demonstration
8
9
Comparison
Advantages of Version 2.0
•
More Economical
•
Easy to use and install
•
Wider Reach (Devnagari Support)
•
More immersive UI
10
Future Scope
•
Personalized calibration for each player
•
Multi linguistic support
•
Dynamic maze generation
11
Q & A
12
Thank You !
13
A study on the development of 3D gesture recognition-based animation games by a team of talented individuals from D.J. Sanghvi College of Engineering and TISS, Mumbai. The project aims to enhance e-learning through interactive, gesture-based games, promoting physical movement and faster learning. It identifies drawbacks in existing systems and introduces Mathmazing Version 2.0, featuring a web camera for gesture capture and a multi-level Blender Game Engine. The workflow improvements from Mathmazing 1.0 to 2.0 include the use of OPENCV for gesture detection.
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Presentation Transcript
Study of 3D Gesture-Recognition Based Animation Game Ishita Shah, Niyati Gosalia, Priya Jain, Abhijit R. Joshi, Neha Katre (D.J. Sanghvi College of Engineering) Sameer Sahasrabuddhe (TISS, Mumbai)
Scope & Purpose Benefits of E-learning : Interactivity Anytime, Anywhere 60% faster learning curve (Facts, Figures and Forces Behind E- Learning ) Bridges gap between student and instructor Benefits of Gesture Based Interactive games : Physical movement during gameplay v/s sedentary gameplay 2
Mathmazing Version 1.0 Developed by - Adeet Shah, Mohini Thakkar, Varun Thakkar (D. J. Sanghvi College of Enginnering) 3
Drawbacks of Existing System Dependency on Kinect Requires NITE, PrimeSense, OpenNi libraries Lack of Devnagari support Lack of Challenge No Instructional tutorial 4
Mathmazing 2.0 Features : Single player Web camera for gesture capture Multi level Blender Game Engine 5
Workflow of Mathmazing 1.0 FAAST Gestures detected by KINECT Key press event passed to .exe of the game Converts gestures into key press events 6
Workflow of Mathmazing 2.0 OPENCV Gestures detected by Camera Key press event passed to .exe of the game Detects and Converts gestures into key press events 7
Comparison Version 1.0 Version 2.0 Kinect (Gesture input) Web Camera (Gesture Input) Does not require any additional libraries, or tools. Requires NITE, PrimeSense, OpenNi libraries Roman Script Devanagari Script Same maze structure for each level Different maze structure for each level No Instructional tutorial Provision for Instructional tutorial 9
Advantages of Version 2.0 More Economical Easy to use and install Wider Reach (Devnagari Support) More immersive UI 10
Future Scope Personalized calibration for each player Multi linguistic support Dynamic maze generation 11
Q & A 12
Thank You ! 13
