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REU: Week 9

REU: Week 9. Overview. Goal: To create a more robust method of classification. Solution: (This Week) Generate Histograms Apply early fusion on histograms. Precomputing Histograms. Generate descriptor vectors. Cluster these descriptors. Generate ‘bag of words’ histograms.

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REU: Week 9

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  1. REU: Week 9

  2. Overview • Goal: To create a more robust method of classification. • Solution: (This Week) • Generate Histograms • Apply early fusion on histograms.

  3. Precomputing Histograms • Generate descriptor vectors. • Cluster these descriptors. • Generate ‘bag of words’ histograms. • These histograms can be combined in a method called early fusion. • Helpful because it will cut down on run times for final run(s).

  4. Histograms • Harris-Laplace and Dense Sampling detectors • SIFT • Scale invariant (only uses intensity channel) • Opponent SIFT • Includes information other than intensity channel, the opponent channels (not intensity invariant) • rgSIFT • Chromacity components r and g describe color information while being intensity invariant.

  5. Fusion • Complementary descriptors chosen to be more robust. • Quite a few papers suggest this gives better results than a single detector. • These histograms are concatenated together before going into the SVM. • Concatenation can be as effective as averaging in circumstances such as these.

  6. Results • The last of the descriptors are being computed and will be available to run histograms on over the weekend. • Code is in place to generate the histograms, as well as ‘fuse’ them before going into the SVM. • Actual results should be available for next week.

  7. Next Week • Results of high-level feature ‘Doorway’ using fusion of histograms. • Combine cross validation code with this week’s work to get some truly meaningful results. • Meaningful in the sense that they should give an accurate portrayal of accuracies to expect.

  8. Questions?

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