Knowledge Commons of Institute of Automation,CAS
View-Angle Invariant Object Monitoring Without Image Registration | |
Zhang, Xin1,2; Huo, Chunlei1,2; Pan, Chunhong1,2 | |
2020-05 | |
会议名称 | IEEE International Conference on Acoustics, Speech and Signal Processing |
会议日期 | 2020-5-4 |
会议地点 | online meeting |
摘要 | Object monitoring can be performed by change detection algorithms. However, for the image pair with a large perspective difference, the change detection performance is usually impacted by inaccurate image registration. To address the above difficulties, a novel object-specific change detection approach is proposed for object monitoring in this paper. In contrast to traditional approaches, the proposed approach is robust to view angle variation and does not require explicit image registration. Experiments demonstrate the effectiveness and advantages of the proposed approach. |
学科门类 | 工学 |
收录类别 | EI |
资助项目 | Beijing Natural Science Foundation[L172053] ; Major Project for New Generation of AI[2018AAA0100400] |
语种 | 英语 |
文献类型 | 会议论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/48536 |
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 | Huo, Chunlei |
作者单位 | 1.NLPR, Institute of Automation, Chinese Academy of Sciences 2.School of Artificial Intelligence, University of Chinese Academy of Sciences |
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 | Zhang, Xin,Huo, Chunlei,Pan, Chunhong. View-Angle Invariant Object Monitoring Without Image Registration[C],2020. |
条目包含的文件 | ||||||
文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
View_angle_invariant(23602KB) | 会议论文 | 开放获取 | CC BY-NC-SA | 浏览 |
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