Lecture 2 Flashcards

1
Q

What is needed to assess the performance of a vision system?

A

Ground truthed data

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2
Q

How should ground truth data be generated?

A

Several experts reaching a consensus

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3
Q

What should be the relationship between data used for developing a system, and that used for testing it?

A

Disjoint - can’t use same data

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4
Q

How do almost all vision systems operate?

A

Take in images and yield labelled results

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5
Q

What are the 4 possible outcomes/statuses of a label?

A

True positive

False positive

True negative

False negative

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6
Q

What is an ROC curve?

A

Receiver-operating characteristic curve:

Plots false positive rate against true positive rate as a tuning parameter is varied

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7
Q

What does a flat line represent on an ROC curve?

A

Random results; a poorly performing algorithm

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8
Q

How do you compare the performance of two algorithms?

A

Statistical test - McNemar’s test

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9
Q

How does McNemar’s test work?

A

Draw a table of Success and Failure for the two algorithms:

Alg 1 Alg 2 S F S Nss Nfs F Nsf Nff

Then Chi2 = (|Nsf-Nfs|-1)^2

(Nsf+Nfs)

If Chi2 > 1.96 the difference in performance is significant at the 5% level

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10
Q

How does content-based image retrieval work?

A

Looks at histograms, similar histograms indicate a match

Can use correlation coefficient on histograms; the closer the result to 1, the closer the image matches

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11
Q

What is the range of values produced by correlation coefficient?

A

-1 <= r <= 1

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12
Q

Give two example graphs for correlation coefficient (values -1 and 1)

A
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13
Q

What is the formula for correlation coefficient?

A
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14
Q

How does a confusion matrix work?

A

Expected along top, actual along side, plot number of occurrences

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