CSE527-l1

CSE527-l1 - CSE527 Introduction to Computer Vision Dimitris...

Info iconThis preview shows pages 1–6. Sign up to view the full content.

View Full Document Right Arrow Icon
1 CSE527 • Introduction to Computer Vision – Dimitris Samaras – Tue thu 5:20-6:40 – CS 2120 Textbooks Computer Vision: A Modern Approach , Forsyth and Ponce, Prentice Hall 2002. (Optional) Introductory Techniques for 3 - D Computer Vision , Trucco and Verri, Prentice Hall 1998. (Optional) Computer Vision: Algorithms and Applications by Richard Szeliski, Microsoft Research: draft at http://research.microsoft.com/en-us/um/ people/szeliski/Book/
Background image of page 1

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon
2 What is Computer Vision? • Inverse Problem of Image Formation • Compute properties of a world (either 2D or 3D from one or more digital images • Geometry • Motion • Recognition Why study Computer Vision? • Images and movies are everywhere • Fast-growing collection of useful applications – representations of the 3D world from pictures – automated surveillance (who’s doing what) – movie post-processing – face finding • Various deep and attractive scientific mysteries – how does object recognition work? • Greater understanding of human vision
Background image of page 2
3 Computer Vision as a sensor • Information about distant objects • Passive Sensor • High bandwidth 1 picture = ? words • Corresponds to the most complex human sensory function • Eat it? Run from it? Mate with it? +more… • Computer Vision is not Animate Vision – Can be inspired though Properties of Vision • One can “see the future” – Cricketers avoid being hit in the head • There’s a reflex --- when the right eye sees something going left, and the left eye sees something going right, move your head fast. – Gannets pull their wings back at the last moment • Gannets are diving birds; they must steer with their wings, but wings break unless pulled back at the moment of contact. • Area of target over rate of change of area gives time to contact.
Background image of page 3

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon
4 Properties of Vision • 3D representations are easily constructed – There are many different cues. – Useful • to humans (avoid bumping into things; planning a grasp; etc.) • in computer vision (build models for movies). – Cues include • multiple views (motion, stereopsis) • texture • shading Properties of Vision • People draw distinctions between what is seen – “Object recognition” – This could mean “is this a fish or a bicycle?” – It could mean “is this George Washington?” – It could mean “is this poisonous or not?” – It could mean “is this slippery or not?” – It could mean “will this support my weight?” – Great mystery • How to build programs that can draw useful distinctions based on image properties.
Background image of page 4
5 Image Sciences Image processing Image to Image Imaging Physics to Image Graphics Symbols to Image Computer Vision Image to Symbols (INVERSE PROBLEM) dA dA’ Relationship with other fields Computer Vision Neuroscience Machine learning
Background image of page 5

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon
Image of page 6
This is the end of the preview. Sign up to access the rest of the document.

This note was uploaded on 11/06/2010 for the course CSE 527 taught by Professor Ab during the Fall '09 term at Cornell.

Page1 / 42

CSE527-l1 - CSE527 Introduction to Computer Vision Dimitris...

This preview shows document pages 1 - 6. Sign up to view the full document.

View Full Document Right Arrow Icon
Ask a homework question - tutors are online