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REU Presentation week: June 4~8

REU Presentation week: June 4~8. Jenny Han. Edge Detection. Calculate the pixel value of the image. {-1, 0, 1} {-2, 0, 2} {-1, 0, 1} Rote the 0s 45s degrees to get the 8 angles and. Cont.

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REU Presentation week: June 4~8

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  1. REU Presentation week: June 4~8 Jenny Han

  2. Edge Detection • Calculate the pixel value of the image. {-1, 0, 1} {-2, 0, 2} {-1, 0, 1} Rote the 0s 45s degrees to get the 8 angles and

  3. Cont. • Generate the image after linear transformation. Use the largest pixel_value out of the 8 for each position. • Find and the max and min value and set a thresh-hold value based on that. • Divide the layout into 5 parts, the center one is overlap: 4 corners and one center.

  4. Cont. 0.021875 0.013542 0.011553 0.009138 0.025710 0.007813 0.005066 0.004972 0.003930 0.007008 0.009422 0.006629 0.004356 0.003977 0.007907 0.017282 0.013400 0.013494 0.009564 0.011080 0.008428 0.008191 0.004924 0.003125 0.008617 0.027509 0.009138 0.014536 0.006013 0.024953 0.008523 0.004687 0.005019 0.001847 0.005824 0.026231 0.016761 0.007907 0.009564 0.007244 0.036080 0.033097 0.019602 0.013447 0.049053 0.006818 0.008759 0.004167 0.006297 0.007244 0.007576 0.010559 ……………………………………………… Keeps going Sample input/output

  5. Edge Histogram

  6. Spatial Pyramid Matching • Spatial pyramid approach can be thought of as an alternative formulation of a locally orderless image, we define a fixed hierarchy of rectangular window

  7. Cont. • Pyramid matching works by placing a sequence of increasingly coarser grids over the feature space and taking a weighted sum of the number of matches that occur at each level of resolution. • At any fixed resolution, two points are said to match if they fall into the same cell of grid

  8. Cont.

  9. Cont. • Classification rate increases when spatial pyramid matching is used. • Will try implement it next week

  10. Reference • “Beyond Bags of Features: Spatial Pyramid Matching for Recognizing Natural Scene Categories” -by Lazebnik, Schmid, & Ponce

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