Conceptual and Experimental Vision

1. Conceptual and Experimental Vision Introduction R.Bajcsy, S.Sastry and A.Yang Fall 2006

2. Introduction and plan for the course • We plan to follow the text :An Invitation to 3-D Vision by Yi Ma, Stefano Soatto,Jana Kosecka and S.S.Sastry. • Plus some additional papers on real time, Active Vision. • Approximately every two weeks there will be a problem set and programming homework assignment • There will no midterm and final, but projects instead. Students are expected to participate in the class.

3. The proposed Syllabus • Week 1: Introduction • Week 2: Image formation : geometry, optics , Radiometry and error analysis • Week 3: Image primitives and correspondence • Week 4: Review of basic algebra and geometry • Week 5 :Epipolar geometry • Week 6: Camera calibration • Week 7: Structure from motion • Week 8: Optimization

4. Syllabus cont., • Week 9: Real Time Vision • Week 10: Visual feedback • Week 11: Active Vision • Week 12: Introduction to GPCA: Iterative methods • Week 13: Introduction to GPCA:Algebraic Methods • Week 14: Estimation and Segmentation of Hybrid Models, and Applications • Week 15:Projects

5. Our expectation • Through this course, students should acquire the ability to study computer vision through rigorous mathematical frameworks. • By the end of the course, students should be familiar with the history of computer vision, the start-of-the-art performance of current vision systems, and important open problems in the literature. • Experimentally, students should be able to setup a stereo camera system, evaluate its characteristics, calibrate it, and reconstruct motions of single and multiple objects.

6. What is Vision? • From the 3-D world to 2-D images: image formation (physics). • Domain of artistic reproduction (synthesis): painting, graphics. • From 2-D images to the 3-D world: image analysis and reconstruction (mathematical modeling, inference). • Domain of vision: biological (eye and brain) computational

7. Topics from a vision conf.: CVPR06

8. CVPR 2006 cont.

9. CVPR 2006 cont.

10. CVPR 2006 cont.

11. What we will cover • Geometry • Stereo and 3D reconstruction • Matching and Registration • Segmentation • Real time considerations • Visual feedback and control • Error analysis of the sensor system

12. What we will not cover • Recognition • Learning • Tracking and video analysis • Low level analysis an graphics and Image Synthesis

13. Our Brain

14. Our eye vs. Camera

15. Multiple views

16. Camera’s multiple views

17. Illusions

18. Illusions for Prof. Ramachandran • http://psy.ucsd.edu/chip/video/Mot_Capt_LQ.rm

19. What painters knew

20. Perspective Imaging and other monocular cues

21. Image Analysis

22. 3-D Modeling and Rendering

23. 3-D Modeling and Rendering

24. Image Mosaicing and panoramic views

25. 3-D reconstruction

26. 3-D data acquisition and reconstruction

27. Geometry and Photometry

28. Compare recovered shape and laser scanned object

29. Data Acquisition and integration of Indian Baskets

30. Real Time Virtual Object Insertion

31. UAV at Berkeley

32. Vision based driving

33. Tele-Immersive environment for Communication