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Dense stereo-based real-Time ROI generation for on-road obstacle detection
- Dense stereo-based real-Time ROI generation for on-road obstacle detection
- Kwon, Soon; Lee, Hyuk-Jae
- DGIST Authors
- Kwon, Soon
- Issue Date
- 13th International SoC Design Conference, ISOCC 2016, 179-180
- Article Type
- Conference Paper
- The use of 3D visual information has become widespread as an essential cue for detecting on-road obstacles in ADAS. In this paper, we propose an accurate dense-stereo-based system for the generation of on-road obstacle ROIs. To balance the concerns of computation overhead and algorithm accuracy, this paper presents an efficient depth map generation that combines global stereo matching with depth up-sampling. The entire system has been implemented with a hardware and software partitioning method running on an FPGA and embedded CPU for real-Time processing. The implementation results verify that the proposed stereo vision system efficiently outputs accurate ROI candidates for on-road obstacle detection. © 2016 IEEE.
- Institute of Electrical and Electronics Engineers Inc.
- Related Researcher
computer vision; deep learning; autonomous driving; parallel processing; vision system on chip
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