1. Seminar on Media Technology Computer Vision Albert Alemany Font

2. Outlines ❖ Introduction What is computer vision and why this topic ❖ History of computer vision and related disciplines ❖ Applications Face/smile detection, OCR, object recognition, medical imaging,... ❖ Conclusions ❖ References

3. What is computer vision? ❖ Traffic scene ❖ Number of vehicles ❖ Type of vehicles ❖ Location of closest obstacle ❖ Assessment of congestion ❖ Location of the scene captures ❖... Given an image or more, extract properties of the 3D world

4. Why this topic?

5. Related disciplines

6. History of computer vision ❖ 1950′s – Two dimensional imaging for statistical pattern recognition developed ❖ 1960′s – Roberts begins studying 3D machine vision ❖ 1970′s – MIT’s Artificial Intelligence Lab opens a "Computer Vision" course ❖ 1980’s – New theories and concepts emerging. Shift toward geometry and increased mathematical rigor ❖ 1990’s – Face recognition. Statistical analysis in vogue ❖ 2000’s – Broader recognition. Large annotated datasets available. Video processing starts

7. Finding people in images "Yes" instances

8. Finding people in images "No" instances

9. Face detection ❖ The camera detects faces in a scene and then automatically focus (AF) and optimizes exposure (AE) and, if needed, flash output Face detection in digital cameras

10. Smile detection

11. Optical character recognition (OCR) Technology to convert scanned docs to text

12. Vision-based biometrics http://www.cl.cam.ac.uk/~jgd1000/afghan.html Photographer: Steve McCurry How the Afghan girl was identified by her iris pattern: 1984 - Right eye processed image 2002 - Right eye processed image

13. Object recognition ❖ Google goggles Query image Webpage Matching image ❖ Lincoln Microsoft Research

14. Mimic human behaviour?

15. Limits of human vision

17. Vision evolution Google reCaptcha

18. Making the invisible visible Eulerian Video Magnification for Revealing Subtle Changes in the World SIGGRAPH 2012 http://people.csail.mit.edu/mrub/vidmag/ Raw version

19. Making the invisible visible Eulerian Video Magnification for Revealing Subtle Changes in the World http://people.csail.mit.edu/mrub/vidmag/ Magnified version SIGGRAPH 2012

20. Smart cars www.mobileye.com

21. Medical imaging Image guided surgery3D Imaging

22. Special effects: shape capture The Matrix movies, ESC Entertainment

23. Special effects: shape capture

24. Special effects: motion capture Pirates of the caribbean, Industrial Light and Magic

25. Video-based interaction: gaming Sony Eyetoy Microsoft Natal

26. Image mosaic ❖ 3D from multiple images ❖ 3D from one image ❖ "Big" image from other images/video

27. Image mosaic

28. Supermarket scanner

29. Conclusions

30. References ❖ Richard Szeliski (2010). Computer Vision: Algorithms and Applications. Springer-Verlag. ❖ Gérard Medioni and Sing Bing Kang (2004). Emerging Topics in Computer Vision. Prentice Hall. ❖ Pedram Azad, Tilo Gockel, Rüdiger Dillmann (2008). Computer Vision – Principles and Practice. Elektor International Media BV. ❖ http://people.csail.mit.edu/mrub/vidmag/ http://people.csail.mit.edu/mrub/vidmag/ ❖ http://www.cvpapers.com/ http://www.cvpapers.com/

31. Thank you for your attention