Deep Open Space Segmentation using Automotive Radar
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.
- Publication:
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arXiv e-prints
- Pub Date:
- March 2020
- DOI:
- arXiv:
- arXiv:2004.03449
- Bibcode:
- 2020arXiv200403449E
- Keywords:
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- Electrical Engineering and Systems Science - Signal Processing;
- Computer Science - Computer Vision and Pattern Recognition;
- Computer Science - Machine Learning
- E-Print:
- IEEE MTT-S International Conference on Microwaves for Intelligent Mobility (ICMIM 2020)