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Computer Vision (CSE/EE 576)

Computer Vision (CSE/EE 576). Staff Prof: Steve Seitz ( seitz@cs ) TA: Aseem Agarwala ( aseem@cs ) Web Page http://www.cs.washington.edu/education/courses/cse576/03sp/ Handouts intro lecture filter lecture signup sheet account forms. Today. Overview of Computer Vision

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Computer Vision (CSE/EE 576)

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  1. Computer Vision (CSE/EE 576) • Staff • Prof: Steve Seitz (seitz@cs) • TA: Aseem Agarwala (aseem@cs) • Web Page • http://www.cs.washington.edu/education/courses/cse576/03sp/ • Handouts • intro lecture • filter lecture • signup sheet • account forms

  2. Today • Overview of Computer Vision • Overview of Course • Images & transformations • Readings for this week • Forsyth & Ponce textbook, chapter 7 • Intelligent Scissors • http://www.cs.washington.edu/education/courses/576/03sp/readings/mort-sigg95.pdf

  3. Every picture tells a story • Goal of computer vision is to write computer programs that can interpret images

  4. Can computers match human perception? • Not yet • computer vision is still no match for human perception • but catching up, particularly in certain areas

  5. Perception

  6. Perception

  7. Perception

  8. Low level processing • Low level operations • Image enhancement, feature detection, region segmentation

  9. Mid level processing • Mid level operations • 3D shape reconstruction, motion estimation

  10. High level processing • High level operations • Recognition of people, places, events

  11. Application: Document Analysis Digit recognition, AT&T labs http://www.research.att.com/~yann/

  12. Applications: 3D Scanning • Scanning Michelangelo’s “The David” • The Digital Michelangelo Project • - http://graphics.stanford.edu/projects/mich/ • UW Prof. Brian Curless, collaborator • 2 BILLION polygons, accuracy to .29mm

  13. Applications: Motion Capture, Games

  14. Application: Medical Imaging

  15. Applications: Robotics

  16. Project 1: Intelligent Scissors

  17. Project 2: Panorama Stitching • http://www.cs.washington.edu/homes/allen/cse590ss/fridge-big.html

  18. Project 3: Face Recognition

  19. Project 4 • Open-ended research project

  20. Class Webpage • http://www.cs.washington.edu/education/courses/cse455/03wi/

  21. Grading • Programming Projects • image scissors • panoramas • face recognition • final project • one or two written homeworks • no final

  22. General Comments • Prerequisites—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. • Emphasis on programming projects!

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