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Deep Open Space Segmentation using Automotive Radar

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arxiv 2004.03449 v1 pith:FJHSEKAX submitted 2020-03-18 eess.SP cs.CVcs.LG

Deep Open Space Segmentation using Automotive Radar

classification eess.SP cs.CVcs.LG
keywords radardeepmodelsopensegmentationspaceachievesadvanced
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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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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