Seminar on Media Technology

Computer Vision

Albert Alemany Font

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

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

Related disciplines

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

Finding people in images"Yes"

instances

Finding people in images"No"

instances

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

Smile detection

Optical character recognition (OCR)

Technology to convert scanned docs to text

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

Object recognition

Google goggles

Query image

Webpage

Matching image

Lincoln Microsoft Research

Mimic human behaviour?

Limits of human vision

Limits of human vision

Vision evolution

Google reCaptcha

Making the invisible visible

Eulerian Video Magnification for Revealing Subtle Changes in the WorldSIGGRAPH

2012http://people.csail.mit.edu/mrub/

vidmag/

Raw version

Making the invisible visible

Eulerian Video Magnification for Revealing Subtle Changes in the Worldhttp://people.csail.mit.edu/mrub/

vidmag/

Magnified version

SIGGRAPH 2012

Smart cars

www.mobileye.com

Medical imaging

Image guided surgery

3D Imaging

Special effects: shape capture

The Matrix movies, ESC Entertainment

Special effects: shape capture

Special effects: motion capture

Pirates of the caribbean, Industrial Light and Magic

Video-based interaction: gaming

Sony Eyetoy

Microsoft Natal

Image mosaic

3D from multiple images 3D from one image "Big" image from other

images/video

Image mosaic

Supermarket scanner

Conclusions

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://www.cvpapers.com/

Thank you for your attention