47 lines
No EOL
1.1 KiB
Markdown
47 lines
No EOL
1.1 KiB
Markdown
#### Object recognition
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Different types of recognition
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- object identification
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- object classification
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##### Which level is right for Object Classes?
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- Basic-Level Categories
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###### Challenges
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- multi-view: different view points
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- multi-class: different types of the same object (different car models)
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- varying illumination
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- ecc
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### Filtering basics
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- Linear filtering
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- Gaussian filtering
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- Multi scale image representation
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- gaussian pyramid
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- edge detection
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- recognition using line drawings
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- image derivatives (1st and 2nd order)
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- object instance identification using color histograms
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- performing evaluation
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probabilità dadi
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$Px(5) = 1/6$
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$Py(5) = 1/6$
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$Px+y(5) = ?$
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We can count the possible cases
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total cases: $6*6=36$
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| 6 | 7 | 8 | 9 | 10 | 11 | 12 |
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| --- | --- | --- | --- | --- | --- | --- |
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| 5 | 6 | 7 | 8 | 9 | 10 | 11 |
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| 4 | 5 | 6 | 7 | 8 | 9 | 10 |
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| 3 | 4 | 5 | 6 | 7 | 8 | 9 |
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| 2 | 3 | 4 | 5 | 6 | 7 | 8 |
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| 1 | 2 | 3 | 4 | 5 | 6 | 7 |
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| | 1 | 2 | 3 | 4 | 5 | 6 |
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possible cases: $P(3)P(1)+P(2)P(2)+P(1)P(3)$
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$P[x*y](S) = $ |