1. KINECT MOTION
TECHNOLOGY

2. CONTENTS
INTRODUCTION
LITERATURE SURVEY
CONCEPTS
REAL TIME CASE STUDIES
APPLICATIONS
COMPARISONS
ADVANTAGES AND DISADVANTAGES
RESULT ANALYSIS
CONCLUSIONS
REFERENCES

3. INTRODUCTION
Kinect motion technology uses a sensor device called
kinect,a 3D scanner which interprets 3D scene information
from a continuously projected infrared structured light.
Is used for:
–Xbox 360 console
–Windows PCs
–Robots

4. Contd
Kinect was developed by microsoft .
Enables users to control and interact with the
application/game.
–Without the need to touch a game controller .
–Through a natural user interface .
–Using gestures and spoken commands .

5. What is NUI ?
Natural User Interface:
 An Invisible Interface
Direct Manipulation
 Gestural interfaces

6. LITERATURE SURVEY
 PAPER 1
Skeleton Tracking using Kinect Sensor &Displaying in 3D
Virtual Scene
-ChanjiraSinthanayothin, Nonlapas Wongwaen, Wisarut
Bholsithi.
(IJACT-2012).

7. PAPER 2
Motion Detection Real Time 3D Walkthrough in Limkokwing
University of Creative Technology (Modet-Walk) using
Kinect XBox
-Behrang Parhizkari,Kanammal Sandrasekaran and Arash
Habibi Lashkari(IJCSI-2012).

8. KINECT SYSTEM
Consists of:
3D Depth sensor
 RGB camera
Motorized tilt
Multi-array microphones

9. KINECT SENSOR

10.  3-D depth sensors
Three-dimensional sensors tracks the body within the play
space.
 RGB camera
An RGB (640 × 480) pixels
helps identify and takes in-game pictures and videos.
Multiple microphones
An array of microphones along the bottom, front edge of the
Kinect sensor are used for speech recognition and chat.
Motorized tilt
A mechanical drive in the base of the Kinect sensor

11. PrimeSense 3D sensing
technology

12. Kinect Features
Full-body 3D motion capture
Gesture recognition
Facial recognition
Voice recognition capabilities

13. Light Coding With Kinect:
Structured light is a form of active
triangulation.
In structured light,a known pattern
is projected onto the scene, and the
depth is calculated on the basis of the
triangulation between a known reference
pattern and observed reflected pattern.

14. Working:
Depth perception using the infrared camera

15. Methodology

16. Detected face and upper body regions in the RGB image

17. Software:
The poses of human skeleton is recognized with the help
of machine learning algorithm called decision tree .
Construction of skeleton
image

18. CASE STUDY
The TurtleBot is a customizable mobile robotic platform
that rides on an iRobot Create platform .
The TurtleBot uses the Kinect to see the world in 3D and
for detecting and tracking people.

19. APPLICATIONS
Health Care
Virtual Piano
DepthJS

20. COMPARISIONS:
Topic NUI GUI
Ease User can learn features
easily through natural
movements
New users may have a
difficult time learning to
use the mouse and all
GUI features.
Speed Depends on the user User must operate using
mouse and keyboard
Strain No strain Shortcut keys are used
Example 3D immersive touch Gnome shell

21. ADVANTAGES
No Data Input Device Required
Voice Recognition
Facial Recognition
Portable

22. DISADVANTAGES
Sensitive to external infrared source (sunlight).
Cannot detect crystalline or highly reflective objects.

23. RESULT ANALYSIS
Detection and tracking of one or two people moving in
the field of view of the sensor, using the tracking of parts
of the skeleton.
Capture audio with noise and echo cancellation.
Speech Recognition.

24. CONCLUSION
This technique aims to provide an application that uses
gestures to interact with virtual objects in an Augmented
Reality application.
 Providing a way for using the gesture-based
interactions to manage operations in a virtual walkthrough
environment is a promising approach.

25. REFERENCES
[1] http://www.wired.com/wiredscience/hacked-
kinect-science/
[2] http://en.wikipedia.org/wiki/Kinect
[3]
http://electronics.howstuffworks.com/microsoft-
kinect.html
[4] http://www.microsoft.com/en-
us/kinectforwindows/

26. THANK YOU

27. QUERIES?