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Web Page• http://www.cs.washington.edu/education/courses/csep576/15sp/

Handouts• signup sheet

Computer Vision (CSE P576)

Prof. Steve Seitzseitz@cs

T.A. Ricardo Martinrmartin@cs@

T.A. Igor Mordatchmordatch@cs

Today• Intros• Computer vision overview• Course overview• Image processing• Features

Readings for this week• Book: Richard Szeliski, Computer Vision: Algorithms and Applications• Ch 1.0, 3.1-3.2, 4.1

What is computer vision? What is computer vision?

Terminator 2

Every picture tells a story

Goal of computer vision is to write computer programs that can interpret images

What do computers see?

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slide by Larry Zitnick

Can computers match (or beat) human vision?

Yes and no (but mostly no!)• humans are much better at “hard” things• computers can be better at “easy” things

Human perception has its shortcomings…

Sinha and Poggio, Nature, 1996

Copyright A.Kitaoka 2003

Current state of the artThe next slides show some examples of what

current vision systems can do

3D Maps

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Games

Microsoft’s XBox Kinect

Face detection

Most digital cameras detect faces

Face recognition

Who is she?

Vision-based biometrics

“How the Afghan Girl was Identified by Her Iris Patterns” Read the story

Object recognition

Google GogglesBing Vision

The Matrix movies, ESC Entertainment, XYZRGB, NRC

Special effects: shape capture Sports

Sportvision first down lineNice explanation on www.howstuffworks.com

Smart cars

Mobileye• Vision systems currently in high-end BMW, GM, Volvo models

Slide content courtesy of Amnon Shashua

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Self-driving cars

“Our self-driving cars have now traveled nearly 200,000 miles on public highways in California and Nevada, 100 percent safely. They have driven from San Francisco to Los Angeles and around Lake Tahoe, and have even descended crooked Lombard Street in San Francisco. They drive anywhere a car can legally drive.”

- Sebastian Thrun, Google

Robotics

http://www.robocup.org/NASA’s Mars Spirit Roverhttp://en.wikipedia.org/wiki/Spirit_rover

Virtual Reality

Microsoft Hololens

Google Cardboard

Current state of the artYou just saw examples of current systems.

• Many of these are less than 5 years old

This is a very active research area, and rapidly changing• Many new apps in the next 5 years

To learn more about vision applications and companies• David Lowe maintains an excellent overview of vision

companies– http://www.cs.ubc.ca/spider/lowe/vision.html

This coursehttp://www.cs.washington.edu/education/courses/csep576/15sp/

Project 1: Features Project 2: Panoramas

Indri Atmosukarto, 576 08sp

Project 3: 3D Shape Reconstruction Project 4: Face Recognition

GradingProgramming Projects (100%)

• features• panoramas• 3D shape modeling• face recognition

General CommentsPrerequisites—these are essential!

• Data structures• A good working knowledge of C and C++ programming• Linear algebra • Vector calculus

Course does not assume prior imaging experience• computer vision, image processing, graphics, etc.