中国科学院机构知识库网格系统: 检索

浏览/检索结果: 共5条，第1-5条

帮助

条数/页：排序方式：
	Robust 3D Model Reconstruction Based on Continuous Point Cloud for Autonomous Vehicles 期刊论文 OAI收割 SENSORS AND MATERIALS, 2021, 卷号: 33, 期号: 9, 页码: 3169-3186 作者: Gao HW(高宏伟); Yu, Jiahui; Sun, Jian; Yang, Wei; Jiang, Yueqiu \| 收藏 \| 浏览/下载：35/0 \| 提交时间：2021/10/01 dense 3D point cloud region growing match optimization monocular zoom stereo vision
	Robust Match Fusion Using Optimization 期刊论文 OAI收割 ieee transactions on cybernetics, 2015, 卷号: 45, 期号: 8, 页码: 1549-1560 作者: Qin, Xiameng; Shen, Jianbing; Mao, Xiaoyang; Li, Xuelong; Jia, Yunde 收藏 \| 浏览/下载：108/0 \| 提交时间：2015/09/09 Exposure fusion moving scenes optimization patch-based match random walker
	Structured-Patch Optimization for Dense Correspondence 期刊论文 OAI收割 ieee transactions on multimedia, 2015, 卷号: 17, 期号: 3, 页码: 295-306 作者: Qin, Xiameng; Shen, Jianbing; Mao, Xiaoyang; Li, Xuelong; Jia, Yunde 收藏 \| 浏览/下载：38/0 \| 提交时间：2015/07/15 Dense correspondence features match optimization structured patch
	The registration of aerial infrared and visible images (EI CONFERENCE) 会议论文 OAI收割 2010 International Conference on Educational and Information Technology, ICEIT 2010, September 17, 2010 - September 19, 2010, Chongqing, China 作者: Liu J.; Wang Y.; Wang Y.; Wang Y.; Wang Y. 收藏 \| 浏览/下载：30/0 \| 提交时间：2013/03/25 In order to solve the registration problem of different source image existed on aerial image fusion algorithms based on Particle Swarm Optimization (PSO) are applied as search strategy in this paper and Alignment Metric (AM) is used as judgment. This study has realized the different source image registration of infrared and visible light with high speed high accuracy and high reliability. Basically with little restriction of gray level properties a new alignment measure is applied which can efficiently measure the image registration extent and tolerate noise well. Even more the intelligent optimization algorithm - Particle Swarm Optimization (PSO) is combined to improve the registration precision and rate of infrared and visible light. Experimental results indicate that the study attains the registration accuracy of pixel level and every registration time is cut down over 40 percent compared to traditional method. The match algorithm based on AM solves the registration problem that greater differences between different source images are existed on gray and characteristic. At the same time the adoption of combining the intelligent optimization algorithms significantly improves the searching efficiency and convergence speed of the algorithms and the registration result has higher accuracy and stability which builds up solid foundation for different source image fusion. The method in this paper has a magnificent effect and is easy for application and very suitable for engineering use. 2010 IEEE.
	Fast covariance matching based on Genetic Algorithm (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 L.; Zhang L.; Zhang X.; Zhang X. 收藏 \| 浏览/下载：17/0 \| 提交时间：2013/03/25 This paper proposes an effective framework to boost the efficiency of covariance matching. In this framework covariance matrices are used to match object in complex environment by fusing multiple features. Then Genetic Algorithm (GA) is employed to improve the processing speed of covariance matching. To take advantage of the property of GA for the optimization in large search spaces to covariance matching a fitness function is designed using the distances between the covariance matrices of model and candidate regions. Experimental results show that the proposed approach can improve the processing speed of covariance matching observably. The computing speed of the proposed method is at least 7 times than that of exhaustive searching. 2010 IEEE.