1. Enhanced Computer Vision with
Microsoft Kinect Sensor: A Review
Jungong Han, Member, IEEE, Ling Shao,Senior Member,
IEEE, Dong Xu, Member, IEEE,
And Jamie Shotton, Member, IEEE
Presenter: Abu Saleh Md Musa
Roll no: 0907013

2. Covered Areas
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Kinect Mechanism
Preprocessing
Object Tracking and Recognition
Human Activity Analysis
Hand Gesture Analysis
Indoor 3-D Mapping
Problems, Outlook and Conclusion

3. Kinect Mechanism
1. Kinect Sensing Hardware

4. Kinect Mechanism
2. Kinect Software Tools

5. Kinect Mechanism
3. Kinect Performance Evaluation
Kinect Censor >TOF cameras

6. Preprocessing
 Kinect Recalibration
 Depth Data Filtering

7. Object Tracking and Recognition
 Object Detection and Tracking
 Object and Scene Recognition

8. Object Tracking and
Recognition

9. Human Activity Analysis
 Pose Estimation
 Activity Recognition

10. Hand Gesture Analysis
 Hand Detection
 Hand Pose Estimation
 Gesture Classification

11. Indoor 3-D Mapping
 Sparse Feature Matching
 Dense Point Matching

12. Problems, Outlook and
Conclusion
 Real-World Applications
 Efficient Integration of Algorithms
 Information Fusion
 Outlook for the Future

13. References
 http://vision.in.tum.de/research/rgb-d_sensors_kinect
 http://www.metrilus.de/range-imaging/time-of-flightcameras/
 http://www.cs.washington.edu/rgbd-dataset/
 http://en.wikipedia.org/wiki/Kinect