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	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: Sun H.; Han H.-X.; Sun H. 收藏 \| 浏览/下载：63/0 \| 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).
	基于表演的2维角色动画技术研究期刊论文 OAI收割中国图象图形学报A, 2010, 卷号: 15, 期号: 9, 页码: 1285-1290 余春龙; 王丹力 \| 收藏 \| 浏览/下载：14/0 \| 提交时间：2011/05/23 基于表演的动画新手或非专业人员逆向运动学角色(人动物) 表演角色动画动画技术专业人员动画系统非专业运动映射运动过程人员使用评估结果技术开发动画制作动画角色低自由度自然直观物体问题实时生成performance-based animation novices and non-professional animators inverse kinematics character(human animal)
	基于人工神经网络的手写汉字识别系统学位论文 OAI收割工学博士, 中国科学院自动化研究所: 中国科学院自动化研究所, 1999 作者: 王春恒收藏 \| 浏览/下载：122/0 \| 提交时间：2015/09/02 手写体汉字识别综合集成人机集成人工神经网络监督学习 handwritten Chinese character recognition Metasynthesis human-machine integration artificial neural network supervised Learning
	Handwritten Chinese character recognition by metasynthetic approach 期刊论文 OAI收割 PATTERN RECOGNITION, 1997, 卷号: 30, 期号: 8, 页码: 1321-1328 作者: Hao, HW; Xiao, XH; Dai, RW \| 收藏 \| 浏览/下载：24/0 \| 提交时间：2018/10/10 Metasynthesis Handwritten Chinese Character Recognition (Hccr) IntegratiOn Based On a Linear Model (Ilm) Network IntegratiOn Based On Supervised Learning (Nisl) Human-machine Integration