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Design and development of autonomous robotic fish for object detection and tracking 期刊论文
International Journal of Advanced Robotic Systems, 2020, 卷号: 17, 期号: 3, 页码: 1-11
作者:  Ji DX(冀大雄);  Rehman, Faizan ur;  Ajwad, Syed Ali;  Shahani, K.;  Sharma, Sanjay
收藏  |  浏览/下载：9/0  |  提交时间：2020/06/13
Real-Time Lane-Vehicle Detection and Tracking System 会议论文
中国银川, 2016-5-28
作者:  Huang G(黄冠);  Wang Xingang;  Wu Wenqi;  Zhou Han;  Wu Yuanyuan
收藏  |  浏览/下载：15/0  |  提交时间：2016/06/28
车辆检测与跟踪系统的设计与实现 学位论文
2016, 2016
李娇
收藏  |  浏览/下载：5/0  |  提交时间：2017/06/20
On-Road Vehicle Detection and Tracking Using MMW Radar and Monovision Fusion 期刊论文
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2016, 卷号: 17, 期号: [db:dc_citation_issue], 页码: 2075-2084
作者:  Wang, Xiao;  Xu, Linhai;  Sun, Hongbin;  Xin, Jingmin;  Zheng, Nanning
收藏  |  浏览/下载：9/0  |  提交时间：2019/12/02
Traffic flow detection system based on video image processing 期刊论文
2010, 2010
Zhang Jie-ying; Wang Sheng-jin; Ding Xiao-qing
收藏  |  浏览/下载：3/0
A vehicle tracking system based on wireless sensor network 期刊论文
2010, 2010
Wang Yong-cai; Wang Chun; Tang Wen; Zhao Qian-chuan; Zheng Da-zhong; Guan Xiao-hong
收藏  |  浏览/下载：4/0
Real-time motive vehicle detection with adaptive background updating model and HSV colour space (EI CONFERENCE) 会议论文
4th International Symposium on Advanced Optical Manufacturing and Testing Technologies: Optical Test and Measurement Technology and Equipment, November 19, 2008 - November 21, 2008, Chengdu, China
Rong-Hui Z.; Bai Y.; Hong-guang J.; Chen T.
收藏  |  浏览/下载：59/0  |  提交时间：2013/03/25
In the transportation monitor system  we set up the area of interest (AOI) of the vehicle model and adjust the size of AOI dynamically in order to track vehicle accurately. The results of experiment show that  motive vehicle detection by adopting digital image is one of key technologies. To detect motive vehicle accurately  the arithmetic proposed in the paper can suppress shadow availably  we establish an adaptive background updating model firstly. Noise is suppressed by using modality filter  detect motive vehicle accurately and satisfy real-time motive vehicle tracking. 2009 SPIE.  and we obtain binary image by using maximum entropy to choose dynamic adaptive threshold. Based on positive information of shadow and aspect feature of motive vehicle  we adopt HSV colour space and double threshold to solve the problem of vehicle shadow. According to prediction result of Kalman filtering  
路面运动目标检测和跟踪技术研究 学位论文
工学博士, 中国科学院自动化研究所: 中国科学院研究生院, 2008
作者:  李书晓
收藏  |  浏览/下载：34/0  |  提交时间：2015/09/02
智能交通中基于视频的交通流参数测量研究 学位论文
工学博士, 中国科学院自动化研究所: 中国科学院研究生院, 2006
作者:  白洪亮
收藏  |  浏览/下载：41/0  |  提交时间：2015/09/02

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