In this work, we propose the use of radar with advanced deep segmentation models to identify open space in parking scenarios. A publically available dataset of radar observations called SCORP was collected. Deep models are evaluated with various radar input representations. Our proposed approach achieves low memory usage and real-time processing speeds, and is thus very well suited for embedded deployment.


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    Title :

    Deep Open Space Segmentation using Automotive Radar




    Publication date :

    2020-11-23


    Size :

    571562 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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