机构

• 长春光学精密机械与物... [2]

采集方式

• OAI收割 [2]

内容类型

• 会议论文 [2]

发表日期

• 2013 [1]
• 2011 [1]

学科主题

筛选

浏览/检索结果: 共2条，第1-2条 帮助 条数/页： 5101520253035404550556065707580859095100 排序方式： 请选择题名升序题名降序发表日期升序发表日期降序提交时间升序提交时间降序作者升序作者降序 Data normalization of single camera visual measurement network system (EI CONFERENCE) 会议论文  OAI收割 2012 International Conference on Information Technology and Management Innovation, ICITMI 2012, November 10, 2012 - November 11, 2012, Guangzhou, China 作者:  Zhang Y.-C.;  Zhou J. 收藏  |  浏览/下载：26/0  |  提交时间：2013/03/25 With the development of visual measurement system  Normalize the measured coordinates into the same world coordinate system  Apply in the three coordinate measuring machine(CMM) to have the simulation experiment  So the data normalization has the advantage of more high precision. (2013) Trans Tech Publications  the visual measurement system of single camera which applied in the imaging theory of optical feature points  then get the global data  the result indicates that the maximum absolute tolerance between the normalization coordinates via the center of point set and the ones measured by CMM directly is 0.058mm  Switzerland.  it has been widespread used in the modern production. Due to the limit of the environment in scene  and achieve the overall measurement  the visual measurement system of single camera could not measure the shield between the measured objects each other. Focus on this problem  But the one between the coordinate repeatedly measured at the position of one network control point is 0.066mm  present a kind of the the knowledge of measurement network based on the visual measurement of single camera  set up the measurement network system via the multi-control points. Measure the optical feature points in every network control point via the visual measurement system of single camera   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).