中国科学院机构知识库网格系统: 检索

浏览/检索结果: 共4条，第1-4条

帮助

条数/页：排序方式：
	Tracking-by-Fusion via Gaussian Process Regression Extended to Transfer Learning 期刊论文 OAI收割 IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2020, 卷号: 42, 期号: 4, 页码: 939-955 作者: Gao, Jin; Wang, Qiang; Xing, Junliang; Ling, Haibin; Hu, Weiming \| 收藏 \| 浏览/下载：40/0 \| 提交时间：2020/06/02 Task analysis Correlation Target tracking Probability distribution Visualization Collaboration Visual tracking Gaussian processes correlation filters transfer learning tracking-by-fusion
	Image registration based on Mexican-hat wavelets and pseudo-Zernike moments (EI CONFERENCE) 会议论文 OAI收割 2012 World Automation Congress, WAC 2012, June 24, 2012 - June 28, 2012, Puerto Vallarta, Mexico 作者: Liu Y.; Liu Y.; Liu Y. 收藏 \| 浏览/下载：40/0 \| 提交时间：2013/03/25 Image registration is a key technique in pattern recognition and image processing and it is widely used in many application areas such as computer vision remote sensing image fusion and object tracking. A method for image registration combining Mexican-hat wavelets and pseudo-Zernike moments is proposed. Firstly feature points are extracted using scale-interaction Mexican-hat wavelets in the reference image and sensed image respectively. Then pseudo-Zernike moments are used to match them and classical RANSAC used to eliminate the wrong matches. And then the well match points are used to estimate the best affine transform parameters by least squares minimization. At last the sensed image is transformed and resampled to accomplish the image registration. The experiments indicate that the proposed algorithm extracts feature points and matches them exactly and eliminates wrong matched points effectively and achieves nice registration results. 2012 TSI Press.
	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).
	Application of multi-sensors parallel fusion system in photoelectric tracing (EI CONFERENCE) 会议论文 OAI收割 2008 International Conference on Optical Instruments and Technology: Optoelectronic Measurement Technology and Applications, November 16, 2008 - November 19, 2008, Beijing, China Cheng G.-Y.; Cai S.; Gao H.-B.; Zhang S.-M.; Qiao Y.-F. 收藏 \| 浏览/下载：24/0 \| 提交时间：2013/03/25 To solve the real-time and reliability problem of tracking servo-control system in optoelectronic theodolite a multisensors parallel processing system was proposed. Misdistances of three different wavebands were imported into system and then prediction was done in DSP1 to get the actual position information. Data fusion was accomplished in PPGA imported by multi channel buffer serial port. The compound position information was used to control the theodolite. The results were compared with external guide data in DSP2 to implement correction of above calculation and then were imported to epistemic machine through PXI interface. The simulation experiment of each calculation unit showed that this system could solve the real-time problem of feature level data fusion. The simulation result showed that the system can satisfy the real-time requirement with 1.25ms in theodolite with three imaging systems while sampling frequency of photoelectric encoder was 800 Hz. 2009 SPIE.