1 / 29

NMF Demo: Lee, Seung

NMF Demo: Lee, Seung. Bryan Russell 6.899 Computer Demonstration. Overview. Training sets Faces Random noise “Block world” Cars Issues/Choices Rank Number of iterations Dataset. NMF: Equations. Objective Function:. NMF: Equations. Update equations:. Faces.

terryal
Télécharger la présentation

NMF Demo: Lee, Seung

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. NMF Demo: Lee, Seung Bryan Russell 6.899 Computer Demonstration

  2. Overview • Training sets • Faces • Random noise • “Block world” • Cars • Issues/Choices • Rank • Number of iterations • Dataset

  3. NMF: Equations • Objective Function:

  4. NMF: Equations • Update equations:

  5. Faces • Training set: 2429 examples • First 25 examples shown at right • Set consists of 19x19 centered face images

  6. Faces • Basis Images: • Rank: 49 • Iterations: 50

  7. Faces Original = x

  8. Faces • Basis Images • Rank: 49 • Iterations: 500

  9. Faces Original = x

  10. Random • Training set: 2429 examples • First 25 examples listed to the right • Gray-level values generated randomly

  11. Random • Basis Images • Rank: 49 • Iterations: 50

  12. Random Original = x

  13. Random • Basis Images • Rank: 49 • Iterations: 500

  14. Random Original Output

  15. Random Originals (1-25) Output (1-25)

  16. “Blocks” • Training set: 2429 examples • First 25 examples listed to the right • Three “shapes”: squares, rectangles, and circles • Shapes centered at two points in image

  17. “Blocks” • Basis Images • Rank: 25 • Iterations: 408

  18. “Blocks” Original = x

  19. “Blocks” Originals (1-25) Output (1-25)

  20. “Blocks” Output (1-25)

  21. “Blocks” • Basis Images • Rank: 49 • Iterations: 345

  22. “Blocks” Originals (1-25) Output (1-25)

  23. “Blocks” Output (1-25)

  24. Cars • Training set: 200 examples • First 25 examples shown at right • Set consists of car images taken at various orientations

  25. Cars • Basis Images • Rank: 49 • Iterations: 310 • Number of samples: 200

  26. Cars Originals (1-25) Output (1-25)

  27. Cars

  28. Thanks! • CBCL for providing face and car images

  29. For code and data, go to: www.ai.mit.edu/~brussell/courses/6.899/nmf

More Related