Knowledge Commons of Institute of Automation,CAS
Dynamic camera configuration learning for high-confidence active object detection | |
Xu, Nuo1,2![]() ![]() ![]() ![]() ![]() ![]() | |
发表期刊 | NEUROCOMPUTING
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ISSN | 0925-2312 |
2021-11-27 | |
卷号 | 466页码:113-127 |
摘要 | The performance of object detection is closely related to the quality of input images. However, the current image acquisition is purely guided by human visual perception, and such camera imaging process ignores the subsequent application. In this context, detection performance is impacted by imaging configuration and dynamic camera motion. To address the above problems, an active object detection framework is proposed in this paper, which aims to build the bridge between imaging configuration and object detec-tion task. Within the proposed framework, a dynamic camera configuration learning approach is pre-sented based on deep reinforcement learning, where the camera is actively controlled to maximize the detection performance. Through iterated interactions between imaging, control and object detection, the deep gap between perception and cognition in the object detection system is eliminated, and the transformation from physical imaging to purposeful imaging is realized. The effectiveness and advan-tages of the proposed framework are demonstrated in three dynamic environments. (c) 2021 Elsevier B.V. All rights reserved. |
关键词 | Object detection Active object detection Deep reinforcement learning Camera control |
DOI | 10.1016/j.neucom.2021.09.037 |
收录类别 | SCI |
语种 | 英语 |
资助项目 | Natural Science Foundation of China[62071466] ; Natural Science Foundation of China[91438105] ; Natural Science Foundation of China[62076242] ; Natural Science Foundation of China[61976208] ; National Key Research and Development Program of China[2018AAA0100400] |
项目资助者 | Natural Science Foundation of China ; National Key Research and Development Program of China |
WOS研究方向 | Computer Science |
WOS类目 | Computer Science, Artificial Intelligence |
WOS记录号 | WOS:000710154200002 |
出版者 | ELSEVIER |
七大方向——子方向分类 | 目标检测、跟踪与识别 |
国重实验室规划方向分类 | 视觉信息处理 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/46283 |
专题 | 多模态人工智能系统全国重点实验室_先进时空数据分析与学习 |
通讯作者 | Xu, Nuo |
作者单位 | 1.Chinese Acad Sci, Inst Automat, NLPR, Beijing 100190, Peoples R China 2.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China 3.Chinese Acad Sci, Ctr Artificial Intelligence & Robot, HK Inst Sci & Innovat, Beijing, Peoples R China |
第一作者单位 | 模式识别国家重点实验室 |
通讯作者单位 | 模式识别国家重点实验室 |
推荐引用方式 GB/T 7714 | Xu, Nuo,Huo, Chunlei,Zhang, Xin,et al. Dynamic camera configuration learning for high-confidence active object detection[J]. NEUROCOMPUTING,2021,466:113-127. |
APA | Xu, Nuo,Huo, Chunlei,Zhang, Xin,Cao, Yong,Meng, Gaofeng,&Pan, Chunhong.(2021).Dynamic camera configuration learning for high-confidence active object detection.NEUROCOMPUTING,466,113-127. |
MLA | Xu, Nuo,et al."Dynamic camera configuration learning for high-confidence active object detection".NEUROCOMPUTING 466(2021):113-127. |
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Dynamic camera confi(4412KB) | 期刊论文 | 作者接受稿 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
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