reu week iv malcolm collins-sibley mentor: shervin ardeshir
TRANSCRIPT
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REU WEEK IVMalcolm Collins-Sibley
Mentor: Shervin Ardeshir
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GOALS FROM LAST WEEK
• Understanding the occlusion handling code
• Making sure it is handling self-occlusions accurately
• Understanding the format of the output data in the line segments/horizon code
• Running the line segmentation code for all of the images in our dataset and saving all of the output variables in a structure
• Extracting the super pixels from images in the dataset and saving it in a structure
• Computing their pairwise similarities of the super pixels in terms of color and texture
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COMPLETED WORK• Error and inaccuracy fixing with the building projection code
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COMPLETED WORK
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COMPLETED WORK
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COMPLETED WORKSmall changes to the top view map
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COMPLETED WORK
• Probability Mapping• Each image has
one map with each building section covered by a Gaussian filter
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COMPLETED WORK
Binary map of where there is a high probability of the building being there
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COMPLETED WORK
Multiple building binary maps
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COMPLETED WORK
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COMPLETED WORK
• Data Storage
Number four is empty because no buildings were detected
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FUSION – PROPAGATION
• We will build a graph on the super-pixels
• Nodes = Super-pixels (Probability of segment I belonging to a building-f(intersection) )
• Edges = Similarity of the super-pixels in terms of color, texture, location, etc
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COMPLETED WORK
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COMPLETED WORK
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THE NEXT STEP
• Tuning building projections in terms of height.
• Generating KML/KMZ files from google earth containing GPS locations of different buildings/roads
• Fusion between building projection and super-pixilation • First with binary mapping• Next with probability mapping
• Initial fusion results (Belief Propagation)
• Run that fusion on the data set