中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
机构
采集方式
内容类型
发表日期
学科主题
筛选

浏览/检索结果: 共8条,第1-8条 帮助

条数/页: 排序方式:
Single UWB Anchor Aided PDR Heading and Step Length Correcting Indoor Localization System 期刊论文  OAI收割
IEEE ACCESS, IEEE ACCESS, 2021, 2021, 卷号: 9, 9, 页码: 11511-11522, 11511-11522
作者:  
Long, Keliu;  Shen, Chong;  Tian, Chuan;  Zhang, Kun;  Bhatti, Uzair Aslam
  |  收藏  |  浏览/下载:37/0  |  提交时间:2021/03/23
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:60/0  |  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).  
Image parallel processing based on GPU (EI CONFERENCE) 会议论文  OAI收割
2010 IEEE International Conference on Advanced Computer Control, ICACC 2010, March 27, 2010 - March 29, 2010, 445 Hoes Lane - P.O.Box 1331, Piscataway, NJ 08855-1331, United States
作者:  
Wang J.-L.;  Wang J.-L.
收藏  |  浏览/下载:31/0  |  提交时间:2013/03/25
In order to solve the compute-intensive character of image processing  based on advantages of GPU parallel operation  parallel acceleration processing technique is proposed for image. First  efficient architecture of GPU is introduced that improves computational efficiency  comparing with CPU. Then  Sobel edge detector and homomorphic filtering  two representative image processing algorithms  are embedded into GPU to validate the technique. Finally  tested image data of different resolutions are used on CPU and GPU hardware platform to compare computational efficiency of GPU and CPU. Experimental results indicate that if data transfer time  between host memory and device memory  is taken into account  speed of the two algorithms implemented on GPU can be improved approximately 25 times and 49 times as fast as CPU  respectively  and GPU is practical for image processing. 2010 IEEE.  
stroke extraction in cartoon images using edge-enhanced isotropic nonlinear filter 会议论文  OAI收割
9th ACM SIGGRAPH International Conference on VR Continuum and Its Applications in Industry, VRCAI 2010, Seoul, Korea, Republic of, 40878
Huang Mengcheng; Yang Meng; Liuy Fang; Wuz En-Hua
  |  收藏  |  浏览/下载:82/0  |  提交时间:2011/03/31
lightweight particle filters based localization algorithm for mobile sensor networks 会议论文  OAI收割
2nd International Conference on Sensor Technologies and Applications, SENSORCOMM 2008, Cap Esterel, France, August 25,
Li An; Sun Limin; Liu Yan; Ma Jian
  |  收藏  |  浏览/下载:23/0  |  提交时间:2011/06/13
Adaptive noise reduction of InSAR data based on anisotropic diffusion models and their applications to phase unwrapping 会议论文  OAI收割
Wave Propagation, Scattering and Emission in Complex Media, Beijing
Wang, C; Gao, X; Zhang, H
收藏  |  浏览/下载:32/0  |  提交时间:2014/12/07
3-D hurricane boundary layer wind retrieval algorithm for airborne doppler radar measurements 会议论文  OAI收割
2004 IEEE International Geoscience and Remote Sensing Symposium Proceedings: Science for Society: Exploring and Managing a Changing Planet. IGARSS 2004, Anchorage, AK, United states, September 20, 2004 - September 24,2004
Ke, Yinghai; Zhang, Xuehu; Chen, Xiuwan; Yang, Jilong; Esteban, Daniel; Carswell, James; Frasier, Stephen; McLaughlin, David J.; Chang, Paul; Black, Peter; Marks, Frank
收藏  |  浏览/下载:32/0  |  提交时间:2014/12/07
A New Architecture for Hyperspectral Image Processing and Analysis System: Design and Implementation 会议论文  OAI收割
Third International Symposium on Multispectral Image Processing and Pattern Recognition, Beijing, China, October 20, 2003 - October 22,2003
Yu, Jianlin; Hu, Xingtang; Zhang, Bing; Ning, Shunian Source
收藏  |  浏览/下载:21/0  |  提交时间:2014/12/07