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gsv_reprojection_semantic_segm

Tests for the reprojection of semantic segmentation masks in Google Street View Images to check if the aggregation of redundant information improves direct semantic segmentation.

Google Street View images extracted via https://github.com/pcarballeira/gsv_database_creator_fork . In this repository the images can be found in the following path: gsv_reprojection_semantic_segm/imgs/Location/pre/51.5008535,-0.122286/M=DRIVING_S=600x300-jpegs

Semantic segmentation masks extracted via https://github.com/pcarballeira/gsv_semantic_segmentation . In this repository the masks, labelmaps and scoremaps can be found in the following path: gsv_reprojection_semantic_segm/imgs/Location/post/M=DRIVING_S=600x300-jpegs

Requirements

  • Matlab
  • Computer vision toolbox

Set up

Download PanoBasic from https://github.com/yindaz/PanoBasic and copy everything inside this folder.

The code consists of a main script and functions that make the different phases of the process.

  • cleanup_database: Removes images from the database that are not useful for reprojection.
  • coordinates: Obtain the coordinates by class of the images.
  • reprojection: Project the above coordinates in the position indicated according to the heading and pitch.
  • agregation: Integration of the reprojected coordinates on each pixel. Three types of simple aggregations are implemented.
  • matrix2print: Preparation to be able to paint the semantic masks.
  • print_mask: Paint the semantic masks over the target image.
  • metrics: Returns different measures of each aggregation and direct segmentation against the ground truth.

When everything is downloaded and in the right place, you just need to run main.m. You can choose the target heading and pitch.

Results

The code returns the scoremap and labemap of the 3 aggregations. It also returns the semantic masks as follows:

  • Maximum point average agregation alt text
  • Weighted maximum point average agregation alt text
  • Weighted maximum local average agregation alt text

Finally, it shows the metrics of each aggregation and direct segmentation against the ground truth.