1 / 30

CIS 350 Principles and Applications Of Computer Vision

Explore the fundamentals and applications of computer vision with Dr. Rolf Lakaemper, covering image representation, processing techniques, object recognition, image databases, and more. Join us to delve into the world of visual computing.

richardsonrebecca
Download Presentation

CIS 350 Principles and Applications Of Computer Vision

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. CIS 350 Principles and Applications Of Computer Vision Dr. Rolf Lakaemper

  2. May I introduce myself… • Rolf Lakaemper • PhD (Doctorate Degree) 2000 • Hamburg University, Germany • Since 1/2003 Assist. Professor at Department of Computer and Information Sciences, Temple University • Main Research Area: Computer Vision

  3. Computer Vision ?

  4. Computer Vision ? “Computer vision’s great trick is extracting descriptions of the world from pictures or sequences of pictures” (Forsyth/Ponce: Computer Vision)

  5. Pictures/Movies: • How to • Represent • Process / Prepare • Handle • Recognize Objects

  6. Representation • Digital Images • Color Spaces • Gray Images • Binary Images • Geometrical Properties

  7. Representation • Digital Images • Color Spaces • Gray Images • Binary Images • Geometrical Properties

  8. How to process / prepare: • Filters • Edges • Geometric Primitives • Lines, Circles

  9. Low Level Object Handling: • Image / Video Compression • Huffman • JPEG • MPEG • …

  10. Low Level Object Handling: • Object representation

  11. Low Level Object Handling: • Segmentation

  12. Object Recognition: • Color, Texture, Shape

  13. Object Recognition: • Applications • Character recognition • Face Recognition • Shape Recognition (Image Databases)

  14. Central Distance Fourier (MATLAB DEMO)

  15. 3D Distance Histogram (MATLAB DEMO)

  16. ISS – An Image-Database using the ASR – Algorithm Dr. Rolf Lakaemper

  17. The Interface (JAVA – Applet)

  18. The Sketchpad: Query by Shape

  19. The First Guess: Different Shape - Classes

  20. Selected shape defines query by shape – class

  21. Result

  22. Specification of different shape in shape – class

  23. Result

  24. Let's go for another shape...

  25. ...first guess...

  26. ...and final result

  27. Query by Shape, Texture and Keyword

  28. Result

  29. CIS 350 Schedule: We: Introduction to topic Fr: LAB Mo: Discussion

  30. CIS 350 Schedule: We: Introduction to topic Fr: LAB Mo: Discussion

More Related