Computer Vision (CSE
P576)
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Staff |
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Prof: Steve Seitz (seitz@cs ) |
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TA: Jiun-Hung Chen (jhchen@cs) |
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Web Page |
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http://www.cs.washington.edu/education/courses/csep576/05wi/ |
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Handouts |
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signup sheet |
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intro slides |
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image filtering slides |
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image sampling slides |
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Today
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Intros |
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Computer vision overview |
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Course overview |
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Image processing |
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Readings for this week |
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Forsyth & Ponce textbook,
chapter 7 |
Every picture tells a
story
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Goal of computer vision is to
write computer programs that can interpret images |
Can computers match human
perception?
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Yes and no (but mostly no!) |
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humans are much better at
“hard” things |
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computers can be better at
“easy” things |
Perception
Perception
Perception
Low level processing
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Low level operations |
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Image enhancement, feature
detection, region segmentation |
Mid level processing
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Mid level operations |
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3D shape reconstruction, motion
estimation |
High level processing
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High level operations |
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Recognition of people, places,
events |
Image Enhancement
Image Enhancement
Image Enhancement
Application: Document Analysis
Applications: 3D Scanning
Slide 16
Slide 17
Slide 18
Slide 19
Slide 20
Slide 21
Slide 22
Applications: Motion Capture, Games
Slide 24
Application: Medical Imaging
Applications: Robotics
Syllabus
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Image Processing (2 weeks) |
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filtering, convolution |
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image pyramids |
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edge detection |
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feature detection (corners,
lines) |
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hough transform |
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Image Transformation (2 weeks) |
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image warping (parametric
transformations, texture mapping) |
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image compositing (alpha
blending, color mosaics) |
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segmentation and matting
(snakes, scissors) |
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Motion Estimation (1 week) |
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optical flow |
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image alignment |
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image mosaics |
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feature tracking |
Syllabus
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Light (1 week) |
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physics of light |
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color |
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reflection |
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shading |
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shape from shading |
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photometric stereo |
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3D Modeling (3 weeks) |
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projective geometry |
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camera modeling |
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single view metrology |
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camera calibration |
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stereo |
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Object Recognition and
Applications (1 week) |
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eigenfaces |
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applications (graphics,
robotics) |
Project 1: Intelligent Scissors
Project 2: Panorama Stitching
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http://www.cs.washington.edu/education/courses/455/03wi/projects/project2/artifacts/crosetti/index.shtml |
Project 3: 3D Shape Reconstruction
Project 4: Face Recognition
Class Webpage
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http://www.cs.washington.edu/education/courses/csep576/05wi/ |
Grading
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Programming Projects (100%) |
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image scissors |
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panoramas |
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3D shape modeling |
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face recognition |
General Comments
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Prerequisites—these are
essential! |
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Data structures |
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A good working knowledge of C
and C++ programming |
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(or willingness/time to pick it
up quickly!) |
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Linear algebra |
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Vector calculus |
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Course does not assume prior
imaging experience |
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computer vision, image
processing, graphics, etc. |
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