中国科学院机构知识库网格系统: 检索

A Novel Sparse Geometric 3-D LiDAR Odometry Approach 期刊论文 OAI收割
IEEE SYSTEMS JOURNAL, 2021, 卷号: 15, 期号: 1, 页码: 1390-1400
作者: Liang, Shuang; Cao, Zhiqiang; Guan, Peiyu; Wang, Chengpeng; Yu, Junzhi

|

收藏 | 浏览/下载：28/0 | 提交时间：2021/05/06

Laser radar Feature extraction Simultaneous localization and mapping Three-dimensional displays Computational complexity Distance measurement Lighting Line and plane features line-to-line and plane-to-plane associations sparse geometric map 3-D light detection and ranging (LiDAR) odometry

3D Point Cloud Analysis and Classification in Large-Scale Scene Based on Deep Learning 期刊论文 OAI收割
IEEE ACCESS, 2019, 卷号: 7, 页码: 55649-55658
作者: Wang, Lei; Meng, Weiliang; Xi, Runping; Zhang, Yanning; Ma, Chengcheng

|

收藏 | 浏览/下载：106/0 | 提交时间：2019/07/11

CNN feature description matrix geometric features point cloud

Rock mass characteristic of Suanjingzi section in the Beishan Preselected Site of China's high-level radioactive waste disposal 期刊论文 OAI收割
ARABIAN JOURNAL OF GEOSCIENCES, 2019, 卷号: 12, 期号: 24, 页码: -
作者: Wang, Guibin; Wei, Xiang; Huo, Liang; Chen, Shiwan; Hou, Zhenkun

|

收藏 | 浏览/下载：28/0 | 提交时间：2020/04/08

Rock mass Joint geometric features Geological characteristic JSR

Error Analysis and Compensation in Images Stitching for the Mechanically Stitched CCD Aerial Cameras 期刊论文 OAI收割
International Journal of Pattern Recognition and Artificial Intelligence, 2019, 卷号: 33, 期号: 9, 页码: 11
作者: H.P.Kuang; L.N.Zheng; G.Q.Yuan; J.J.Sun; Z.Zhang

|

收藏 | 浏览/下载：31/0 | 提交时间：2020/08/24

Mechanically stitched CCD,error analysis,aerial camera,POS-assisted,geometric correction,features,Computer Science

A generic framework for image rectification using multiple types of feature 期刊论文 OAI收割
ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING, 2015, 卷号: 102, 页码: 2449-2470
作者: Long, Tengfei; Jiao, Weili; He, Guojin; Zhang, Zhaoming; Cheng, Bo

收藏 | 浏览/下载：22/0 | 提交时间：2016/04/20

Geometric Rectification Orientation Multiple features Hausdorff distance Imaging model

An over-segmentation method for single-touching Chinese handwriting with learning-based filtering 期刊论文 OAI收割
INTERNATIONAL JOURNAL ON DOCUMENT ANALYSIS AND RECOGNITION, 2014, 卷号: 17, 期号: 1, 页码: 91-104
作者: Xu, Liang; Yin, Fei; Wang, Qiu-Feng; Liu, Cheng-Lin

收藏 | 浏览/下载：39/0 | 提交时间：2015/08/12

Single-touching strings Chinese handwriting Over-segmentation Learning-based filtering Geometric features

A line mapping based automatic registration algorithm of infrared and visible images 会议论文 OAI收割
5th International Symposium on Photoelectronic Detection and Imaging (ISPDI) - Infrared Imaging and Applications, Beijing, June 25-27, 2013
作者: Ai R(艾锐); Shi ZL(史泽林); Xu DJ(徐德江); Zhang CS(张程硕)

收藏 | 浏览/下载：35/0 | 提交时间：2013/12/26

There exist complex gray mapping relationships among infrared and visible images because of the different imaging mechanisms. The difficulty of infrared and visible image registration is to find a reasonable similarity definition. In this paper, we develop a novel image similarity called implicit linesegment similarity(ILS) and a registration algorithm of infrared and visible images based on ILS. Essentially, the algorithm achieves image registration by aligning the corresponding line segment features in two images. First, we extract line segment features and record their coordinate positions in one of the images, and map these line segments into the second image based on the geometric transformation model. Then we iteratively maximize the degree of similarity between the line segment features and correspondence regions in the second image to obtain the model parameters. The advantage of doing this is no need directly measuring the gray similarity between the two images. We adopt a multi-resolution analysis method to calculate the model parameters from coarse to fine on Gaussian scale space. The geometric transformation parameters are finally obtained by the improved Powell algorithm. Comparative experiments demonstrate that the proposed algorithm can effectively achieve the automatic registration for infrared and visible images, and under considerable accuracy it makes a more significant improvement on computational efficiency and anti-noise ability than previously proposed algorithms.

Geometric Features Sensitive Mesh Segmentation Orient to Patch-based Fitting 会议论文 OAI收割
Mechanical and Electronics Engineering Iii, Pts 1-5, Stafa-Zurich
Zhao Xiang-jun; Lu Mei; Gong Jianhua

收藏 | 浏览/下载：21/0 | 提交时间：2014/12/07

geometric approximation geometric features sensitive segmentation T-splines reconstruction APPROXIMATION

Automatic bridge extraction for optical images (EI CONFERENCE) 会议论文 OAI收割
6th International Conference on Image and Graphics, ICIG 2011, August 12, 2011 - August 15, 2011, Hefei, Anhui, China
Gu D.-Y.; Zhu C.-F.; Shen H.; Hu J.-Z.; Chang H.-X.

收藏 | 浏览/下载：27/0 | 提交时间：2013/03/25

This paper describes a novel hierarchy algorithm for extracting bridges over water in optical images. To reduce the omission of bridges by searching the edge we extract the river regions which the bridges are included in. Firstly we segment the optical image to get the coarse water bodies using iterative threshold eliminate the noise regions and add the missing regions based on k-means clustering with texture information and spatial coherence. Then the blanks are connected based on shape features and candidate bridge regions are segmented from river regions. Finally the bridges are verified by geometric information and the ubiety between bridges and river. The results show that this approach is efficient and effective for extracting bridges in satellite image from Google Earth and in aerial optical images acquired by unmanned aerial vehicle. 2011 IEEE.

EXTRACTION OF OBJECT FEATURES FROM HIGH RESOLUTION SAR IMAGES BASED ON SURF FEATURES 会议论文 OAI收割
2011 Ieee International Geoscience and Remote Sensing Symposium, New York
Tian, Xiaonjuan; Wang, Chao; Zhang, Hong

收藏 | 浏览/下载：20/0 | 提交时间：2014/12/07

Feature Extraction high resolution SAR SURF description geometric features