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Proceedings Paper

Research on autonomous driving perception based on deep learning algorithm
Author(s): Bolin Zhou; Jihu Zheng; Chen Chen; Pei Yin; Yang Zhai
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Paper Abstract

Multiple source sensor fusion is the foundation of motion planning for autonomous driving system, which is the crucial part in improving the performances for unmanned operational system. In this article, based on the deep learning platform CATARC constructed, applied with Udacity’s Lincoln MKZ multiple sensor data, implemented with Robotic Operation System, Computer Vision, PointCloud Library, Deep Neural Networks and Extended Kalman Filter, constructed a low-cost object pose estimation data fusion solution, aiming at technic support for the industrialization of autonomous driving technologies.

Paper Details

Date Published: 27 November 2019
PDF: 8 pages
Proc. SPIE 11321, 2019 International Conference on Image and Video Processing, and Artificial Intelligence, 113210B (27 November 2019); doi: 10.1117/12.2539133
Show Author Affiliations
Bolin Zhou, China Automotive Technology and Research Ctr. Co., Ltd. (China)
Jihu Zheng, China Automotive Technology and Research Ctr. Co., Ltd. (China)
Chen Chen, China Automotive Technology and Research Ctr. Co., Ltd. (China)
Pei Yin, Chang'an Univ. (China)
Yang Zhai, China Automotive Technology and Research Ctr. Co., Ltd. (China)


Published in SPIE Proceedings Vol. 11321:
2019 International Conference on Image and Video Processing, and Artificial Intelligence
Ruidan Su, Editor(s)

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