2018年2月2日
Real-time object classification for autonomous vehicle using LIDAR
ICIIBMS 2017 - 2nd International Conference on Intelligent Informatics and Biomedical Sciences
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- 巻
- 2018-
- 号
- 開始ページ
- 210
- 終了ページ
- 211
- 記述言語
- 英語
- 掲載種別
- 研究論文(国際会議プロシーディングス)
- DOI
- 10.1109/ICIIBMS.2017.8279696
- 出版者・発行元
- Institute of Electrical and Electronics Engineers Inc.
Object classification is an important issue in order to bring autonomous vehicle into reality. In this paper, real-time and robust classification based on Real AdaBoost algorithm is researched and improved. Various effective features of road objects are computed using LIDAR 3D point clouds. The improved classifier provides an accuracy of over 90 (%) in a range of 50 (m) and classifies objects into car, pedestrian, bicyclist and background. Moreover, processing time of classifying an object consumes only 0.0710-3 (sec) that enables this method to be used for autonomous driving on urban roads.
- リンク情報
- ID情報
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- DOI : 10.1109/ICIIBMS.2017.8279696
- SCOPUS ID : 85047391785