Deep Open Space Segmentation using Automotive Radar
arXiv:2004.03449
Abstract
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.
IEEE MTT-S International Conference on Microwaves for Intelligent Mobility (ICMIM 2020)