Embedded Platforms for Computer Vision-based Advanced Driver Assistance Systems: a Survey
April 28, 2015 ยท The Cartographer ยท ๐ arXiv.org
"No code URL or promise found in abstract"
"Title-pattern auto-detect: Embedded Platforms for Computer Vision-based Advanced Driver Assistance Systems: a Survey"
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Authors
Gorka Velez, Oihana Otaegui
arXiv ID
1504.07442
Category
cs.CV: Computer Vision
Citations
6
Venue
arXiv.org
Last Checked
3 days ago
Abstract
Computer Vision, either alone or combined with other technologies such as radar or Lidar, is one of the key technologies used in Advanced Driver Assistance Systems (ADAS). Its role understanding and analysing the driving scene is of great importance as it can be noted by the number of ADAS applications that use this technology. However, porting a vision algorithm to an embedded automotive system is still very challenging, as there must be a trade-off between several design requisites. Furthermore, there is not a standard implementation platform, so different alternatives have been proposed by both the scientific community and the industry. This paper aims to review the requisites and the different embedded implementation platforms that can be used for Computer Vision-based ADAS, with a critical analysis and an outlook to future trends.
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