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Infrared-visible video automatic registration with contour feature matching 期刊论文
Guangxue Jingmi Gongcheng/Optics and Precision Engineering, 2020, 卷号: 28, 期号: 5, 页码: 1140-1151
作者:  X.-L. Sun,G.-L. Han,L.-H. Guo,P.-X. Liu and T.-F. Xu
收藏  |  浏览/下载：2/0  |  提交时间：2021/07/06
目标跟踪中的在线学习方法研究 学位论文
硕士, 沈阳: 中国科学院沈阳自动化研究所, 2017
作者:  李义翠
收藏  |  浏览/下载：40/0  |  提交时间：2017/06/29
Moving target detection based on dynamic background of cellular automaton 期刊论文
Guangxue Jingmi Gongcheng/Optics and Precision Engineering, 2017, 卷号: 25, 期号: 7
作者:  Lu, M.;  M. Zhu;  Y. Gao and L. Zhang
收藏  |  浏览/下载：13/0  |  提交时间：2018/06/13
基于混合高斯模型的日冕物质抛射探测方法 期刊论文
科学通报, 2016, 卷号: 61, 期号: 11, 页码: 1255-1264
作者:  曾丹丹;  白先勇;  强振平;  李强;  季凯帆
收藏  |  浏览/下载：27/0  |  提交时间：2016/07/12
运动目标侵入侦测与跟踪 学位论文
硕士, 中国科学院沈阳自动化研究所: 中国科学院沈阳自动化研究所, 2015
作者:  孙照蕾
收藏  |  浏览/下载：24/0  |  提交时间：2015/08/20
视频图像中运动目标的检测与跟踪算法研究 学位论文
2015, 2014
戴宝燕
收藏  |  浏览/下载：5/0  |  提交时间：2016/01/12
An improved PCNN moving target detection algorithm in complex background circumstances 期刊论文
Journal of Information& Computational Science, 2014, 卷号: 11, 期号: 14, 页码: 5193-5200
作者:  Liu J(刘军)
收藏  |  浏览/下载：0/0  |  提交时间：2020/11/09
Transferring Training Instances for Convenient Cross-View Object Classification in Surveillance 期刊论文
IEEE Transactions on Information Forensics and Security, 2013, 卷号: 8, 期号: 10, 页码: 1632-1641
作者:  Zhaoxiang Zhang;  Yuhang Zhao;  Yunhong Wang;  Jianyun Liu;  Zhenjun Yao
收藏  |  浏览/下载：18/0  |  提交时间：2017/02/09
The new approach for infrared target tracking based on the particle filter algorithm (EI CONFERENCE) 会议论文
International Symposium on Photoelectronic Detection and Imaging 2011: Advances in Infrared Imaging and Applications, May 24, 2011 - May 24, 2011, Beijing, China
Sun H.; Han H.-X.
收藏  |  浏览/下载：50/0  |  提交时间：2013/03/25
Target tracking on the complex background in the infrared image sequence is hot research field. It provides the important basis in some fields such as video monitoring  precision  and video compression human-computer interaction. As a typical algorithms in the target tracking framework based on filtering and data connection  the particle filter with non-parameter estimation characteristic have ability to deal with nonlinear and non-Gaussian problems so it were widely used. There are various forms of density in the particle filter algorithm to make it valid when target occlusion occurred or recover tracking back from failure in track procedure  but in order to capture the change of the state space  it need a certain amount of particles to ensure samples is enough  and this number will increase in accompany with dimension and increase exponentially  this led to the increased amount of calculation is presented. In this paper particle filter algorithm and the Mean shift will be combined. Aiming at deficiencies of the classic mean shift Tracking algorithm easily trapped into local minima and Unable to get global optimal under the complex background. From these two perspectives that "adaptive multiple information fusion" and "with particle filter framework combining"  we expand the classic Mean Shift tracking framework.Based on the previous perspective  we proposed an improved Mean Shift infrared target tracking algorithm based on multiple information fusion. In the analysis of the infrared characteristics of target basis  Algorithm firstly extracted target gray and edge character and Proposed to guide the above two characteristics by the moving of the target information thus we can get new sports guide grayscale characteristics and motion guide border feature. Then proposes a new adaptive fusion mechanism  used these two new information adaptive to integrate into the Mean Shift tracking framework. Finally we designed a kind of automatic target model updating strategy to further improve tracking performance. Experimental results show that this algorithm can compensate shortcoming of the particle filter has too much computation  and can effectively overcome the fault that mean shift is easy to fall into local extreme value instead of global maximum value.Last because of the gray and fusion target motion information  this approach also inhibit interference from the background  ultimately improve the stability and the real-time of the target track. 2011 Copyright Society of Photo-Optical Instrumentation Engineers (SPIE).  
运动目标检测算法的研究 学位论文
2011, 2010
魏针
收藏  |  浏览/下载：3/0  |  提交时间：2016/02/14

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