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Machine Learning Competition Aditya Khosla Image by - PowerPoint PPT Presentation

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6.S093 Visual Recognition through Machine Learning Competition Aditya Khosla Image by kirkh.deviantart.com Todays class Part 1: Competition details Part 2: Image representation lecture Bag-of-words Spatial pyramid Part 3:

  1. 6.S093 Visual Recognition through Machine Learning Competition Aditya Khosla Image by kirkh.deviantart.com

  2. Today’s class • Part 1: Competition details • Part 2: Image representation lecture – Bag-of-words – Spatial pyramid • Part 3: Feature extraction tutorial

  3. Competition details: dataset airplane bicycle car person 10 object categories cup/mug dog(s) guitar hamburger sofa traffic light

  4. Competition details: dataset Validation set 2,000 images Testing set 5,000 images Training set 8,000 images Leaderboard set labels provided NO labels provided

  5. Competition details: submission • For each image, you provide the probability of every class belonging in it (as returned by your algorithm) 1 0 hamburger car cup dog person airplane bicycle guitar sofa traffic light

  6. Competition details: evaluation • Average precision

  7. Competition details: prizes first second third Cash + + cash cash

  8. Competition details: thank you!

  9. Image representation: bag-of-words

  10. Document representation: bag-of-words • Order-less document representation: frequencies of words from a dictionary Salton & McGill (1983)

  11. Document representation: bag-of-words • Order-less document representation: frequencies of words from a dictionary Salton & McGill (1983) US Presidential Speeches Tag Cloud

  12. Document representation: bag-of-words • Order-less document representation: frequencies of words from a dictionary Salton & McGill (1983) US Presidential Speeches Tag Cloud

  13. Document representation: bag-of-words • Order-less document representation: frequencies of words from a dictionary Salton & McGill (1983) US Presidential Speeches Tag Cloud

  14. Image representation: bag-of-words bag-of-words document

  15. Image representation: bag-of-words bag-of-words document image bag-of-visual words

  16. Object Bag of ‘words’

  17. Ugly bag of Object ‘words’

  18. Stylish bag of Object ‘words’

  19. Stylish bag of Object ‘words’

  20. visual dictionary

  21. Image representation: bag-of-words 1. Extract descriptors

  22. Image representation: bag-of-words 1. Extract descriptors 2. Learn “visual dictionary”

  23. Image representation: bag-of-words 1. Extract descriptors 2. Learn “visual dictionary” 3. Quantize features using visual vocabulary

  24. Image representation: bag-of-words 1. Extract descriptors 2. Learn “visual dictionary” 3. Quantize features using visual vocabulary

  25. Image representation: bag-of-words 1. Extract descriptors 2. Learn “visual dictionary” 3. Quantize features using visual vocabulary 4. Represent images by frequencies of “visual words”

  26. 1. Extracting descriptors regular grid interest points

  27. Image representation: yesterday gradient magnitude feature vector gradient orientation

  28. Image representation: yesterday gradient magnitude descriptor gradient orientation

  29. 2. Learning “visual dictionary” Compute descriptor

  30. 2. Learning “visual dictionary” … descriptors

  31. 2. Learning visual dictionary descriptors …

  32. 2. Learning visual dictionary descriptors … Clustering

  33. 2. Learning visual dictionary descriptors visual vocabulary … Clustering

  34. Example visual vocabulary Fei-Fei et al. 2005

  35. Image patch examples Sivic et al. 2005

  36. Image patch examples How to choose the vocabulary size? Sivic et al. 2005

  37. Bag-of-words: limitations • What about the structure of the image? =?

  38. Image representation: spatial pyramids level 0

  39. Image representation: spatial pyramids level 0 level 1

  40. Image representation: spatial pyramids level 0 level 1 level 2

  41. Tutorial

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