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	A Novel Divide and Conquer Solution for Long-term Video Salient Object Detection 期刊论文 OAI收割 Machine Intelligence Research, 2024, 卷号: 21, 期号: 4, 页码: 684-703 作者: Yun-Xiao Li; Cheng-Li-Zhao Chen; Shuai Li; Ai-Min Hao; Hong Qin \| 收藏 \| 浏览/下载：22/0 \| 提交时间：2024/07/18 Video salient object detection background consistency analysis weakly supervised learning long-term information background shift
	Forward-Backward Mean-Shift for Visual Tracking With Local-Background-Weighted Histogram 期刊论文 OAI收割 IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2013, 卷号: 14, 期号: 3, 页码: 1480-1489 作者: Wang, Lingfeng; Yan, Hongping; Wu, Huai-Yu; Pan, Chunhong 收藏 \| 浏览/下载：51/0 \| 提交时间：2015/08/12 Forward-backward mean shift (FBMS) local-background-weighted histogram (LBWH) visual tracking
	利用检测特征空间的目标实时跟踪期刊论文 OAI收割计算机科学, 2013, 卷号: 40, 期号: z2, 页码: 309-313 安国成; 张凤军 \| 收藏 \| 浏览/下载：28/0 \| 提交时间：2014/12/16 实时检测帧间差分背景建模均值移动 Real-time detection Frame differencing Background modeling Mean shift
	The new approach for infrared target tracking based on the particle filter algorithm (EI CONFERENCE) 会议论文 OAI收割 International Symposium on Photoelectronic Detection and Imaging 2011: Advances in Infrared Imaging and Applications, May 24, 2011 - May 24, 2011, Beijing, China 作者: 收藏 \| 浏览/下载：65/0 \| 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).
	The movement estimation of target and background by fourier phase spectrum difference (EI CONFERENCE) 会议论文 OAI收割 2010 6th International Conference on Wireless Communications, Networking and Mobile Computing, WiCOM 2010, September 23, 2010 - September 25, 2010, Chengdu, China 作者: Zhang X.; Zhang X.; Zhang X.; Wang J.; Zhang S. 收藏 \| 浏览/下载：29/0 \| 提交时间：2013/03/25 An algorithm for estimating displacement of the moving target and background by shift theory of Fourier transform is presented. According to the relation between the change and the Fourier transform of image sequence the method employs the displacement value of the moving target and background by the difference of Fourier phase spectrum. The algorithm estimates the movements from the whole field of the image with excellent global property. This paper provides the calculus and experiments of the algorithm which show the accuracy of 1 pixel. 2010 IEEE.
	Adaptive deformation estimation of moving target by weight image analysis (EI CONFERENCE) 会议论文 OAI收割 2010 2nd International Conference on Future Computer and Communication, ICFCC 2010, May 21, 2010 - May 24, 2010, Wuhan, China Bai X.-G.; Dai M. 收藏 \| 浏览/下载：39/0 \| 提交时间：2013/03/25 An algorithm based on weight image analysis is proposed for adaptive deformation estimation of moving target in mean-shift tracking method. At the first we get the weight image from the target candidate region. Then we analyze the differences between the object and background. According to that the area estimation of the target can be converted into the image segmentation task. To realize the adaptive segmentation and estimation we define the threshold as the maximum variance between object and background. Combining the estimated area and covariance matrix we can estimate the width height and orientation of the object. The experimental results on three representative video sequences validate its robustness to the deformable estimation of the targets. 2010 IEEE.
	Nonparametric background generation 期刊论文 OAI收割 JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION, 2007, 卷号: 18, 期号: 3, 页码: 253-263 作者: Liu, Yazhou; Yao, Hongxun; Gao, Wen; Chen, Xilin; Zhao, Debin \| 收藏 \| 浏览/下载：26/0 \| 提交时间：2019/12/16 background subtraction background generation mean shift effect components description most reliable background mode video surveillance
	视频处理中的目标分割与跟踪的研究学位论文 OAI收割工学硕士, 中国科学院自动化研究所: 中国科学院研究生院, 2004 赵宇收藏 \| 浏览/下载：44/0 \| 提交时间：2015/09/02 背景初始化背景减目标分割目标跟踪均值漂移行扫描多类谱聚类监控系统 Background Initialization Background Subtraction Object Segmentation Object Tracking Mean-Shift Row-Scanned Classification Multi