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Detecting Parking Spaces in a Parcel using Satellite Images

Detecting Parking Spaces in a Parcel using Satellite Images

Remote Sensing Images from satellites have been used in various domains for detecting and understanding structures on the ground surface. In this work, satellite images were used for localizing parking spaces and vehicles in parking lots for a given parcel using an RCNN based Neural Network Architectures.Parcel shape files and raster images from USGS image archive was used for developing images for both training and testing. Feature Pyramid based Mask RCNN yields average class accuracy of 97.56% for both parking spaces and vehicles.

Murugesan Vadivel, SelvaKumar Murugan, Suriyadeepan Ramamoorthy Vaidheeswaran Archana, and Malaikannan Sankarasubbu conducted this research for the Saama AI Research team.

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