A Review on Object Detection Based on Deep Convolutional Neural Networks for Autonomous Driving | |
Lu JL(卢佳琳); Tang SM(汤淑明); Wang JQ(王金桥); Zhu HB(朱海兵); Wang YK(王云宽) | |
2019-06-03 | |
会议名称 | Chinese Control and Decision Conference |
会议日期 | 2019-6-3 |
会议地点 | 中国江西省南昌市 |
摘要 | Vehicle and pedestrian detection is significant in autonomous driving. It provides information for path planning, lane selection, pedestrian and vehicle tracking, pedestrian behavior prediction, etc. In recent years, the state-of-the-art object detection algorithms have been emerged on the base of deep convolutional neural networks, which can get higher accuracy and efficiency detection results than traditional vision detection algorithms. In this paper, we first introduce and summarize some state-of-the-date object detection algorithms based of deep convolutional neural networks and the improvement ideas of these algorithms. Their frameworks are extracted. Then, we choose several different algorithms and analyze their running results on challenging datasets, Pascal VOC and KITTI. Next, we analyze the current detection challenges as well as their solutions. Finally, we provide insights into use in autonomous driving, such as vehicle and pedestrian detection and driving control. |
收录类别 | EI |
语种 | 英语 |
文献类型 | 会议论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/23640 |
专题 | 智能制造技术与系统研究中心 |
通讯作者 | Tang SM(汤淑明) |
作者单位 | 中国科学院自动化研究所 |
第一作者单位 | 中国科学院自动化研究所 |
通讯作者单位 | 中国科学院自动化研究所 |
推荐引用方式 GB/T 7714 | Lu JL,Tang SM,Wang JQ,et al. A Review on Object Detection Based on Deep Convolutional Neural Networks for Autonomous Driving[C],2019. |
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文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
CCDC-终稿定稿.pdf(699KB) | 会议论文 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
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