检索结果-内蒙古大学图书馆

您好，读者！请登录

内蒙古大学图书馆

首页
概况
党建
资源
服务
科研支持
- 论文收录引用证明
- 科技查新
知识产权
档案馆
帮助

咨询与建议

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

您的常用邮箱：*

您的手机号码：*

问题描述：

当前已输入0个字，您还可以输入200个字

全部搜索
期刊论文
图书
学位论文
标准
纸本馆藏
外文资源发现
数据库导航
超星发现

高级检索

时间限定

出版年份：

文献类型

图书期刊文献学位论文多媒体

馆藏选择

电子馆藏纸本馆藏

核心期刊

全部期刊 SCI 收录期刊 SSCI 收录期刊 EI 收录期刊 CSCD 收录期刊 CSSCI 收录期刊

语言

中文英文

文献类型

期刊文献图书学位论文标准纸本馆藏

帮助

文字说明：

T=题名（书名、题名），A=作者（责任者），K=主题词，P=出版物名称，PU=出版社名称，O=机构（作者单位、学位授予单位、专利申请人），L=中图分类号，C=学科分类号，U=全部字段，Y=年（出版发行年、学位年度、标准发布年）

检索规则说明：

AND代表“并且”；OR代表“或者”；NOT代表“不包含”；(注意必须大写,运算符两边需空一格)

检索范例：

范例一：(K=图书馆学 OR K=情报学) AND A=范并思 AND Y=1982-2016
范例二：P=计算机应用与软件 AND (U=C++ OR U=Basic) NOT K=Visual AND Y=2011-2016

分类表

所选分类

>> <<

限定检索结果

文献类型

1,565 篇 会议
74 篇 期刊文献
2 篇 学位论文

馆藏范围

1,641 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

504 篇 工学
- 177 篇 电气工程
- 174 篇 计算机科学与技术...
- 134 篇 控制科学与工程
- 121 篇 机械工程
- 81 篇 仪器科学与技术
- 40 篇 软件工程
- 36 篇 生物医学工程（可授...
- 33 篇 信息与通信工程
- 29 篇 电子科学与技术（可...
- 15 篇 生物工程
- 13 篇 交通运输工程
- 8 篇 材料科学与工程（可...
- 6 篇 测绘科学与技术
- 4 篇 光学工程
- 4 篇 航空宇航科学与技...
- 3 篇 建筑学
- 3 篇 公安技术
51 篇 理学
- 27 篇 物理学
- 16 篇 系统科学
- 3 篇 生物学
- 2 篇 数学
- 2 篇 地理学
- 2 篇 地球物理学
50 篇 医学
- 38 篇 临床医学
- 5 篇 特种医学
- 4 篇 基础医学(可授医学...
28 篇 管理学
- 28 篇 管理科学与工程(可...
16 篇 农学
- 15 篇 作物学
9 篇 艺术学
- 9 篇 设计学（可授艺术学...
3 篇 文学
- 3 篇 新闻传播学
1 篇 法学

主题

1,641 篇 iterative closes...
395 篇 three-dimensiona...
250 篇 cameras
232 篇 robustness
219 篇 iterative algori...
212 篇 shape
168 篇 feature extracti...
116 篇 robot sensing sy...
114 篇 simultaneous loc...
109 篇 solid modeling
98 篇 estimation
92 篇 image reconstruc...
90 篇 laser radar
85 篇 iterative method...
82 篇 accuracy
78 篇 face recognition
78 篇 three dimensiona...
77 篇 mobile robots
73 篇 convergence
71 篇 algorithm design...

机构

8 篇 institute of art...
5 篇 department of co...
5 篇 robotics institu...
4 篇 osaka university
4 篇 university of st...
4 篇 xi an jiao tong ...
4 篇 xi an jiao tong ...
4 篇 department of co...
4 篇 microsoft resear...
3 篇 univ bonn bonn
3 篇 robotics institu...
3 篇 princeton univer...
3 篇 department of co...
3 篇 florida inst hum...
3 篇 department of el...
3 篇 university of to...
3 篇 shanghai univ sc...
3 篇 tokyo university...
3 篇 department of co...
3 篇 institute for in...

作者

18 篇 yonghuai liu
13 篇 shaoyi du
11 篇 m.a. rodrigues
7 篇 jianru xue
6 篇 m. greenspan
6 篇 du shaoyi
6 篇 lale akarun
5 篇 mengling feng
5 篇 baogang wei
5 篇 leena ukkonen
5 篇 berk gokberk
5 篇 yang yang
5 篇 andreas nüchter
5 篇 nese alyuz
5 篇 h. hugli
5 篇 jihua zhu
5 篇 wei wang
5 篇 ming yang
4 篇 m. hebert
4 篇 angelos mallios

语言

1,631 篇 英文
8 篇 中文
2 篇 其他

检索条件"主题词=iterative closest point algorithm"

共 1641 条记录，以下是81-90 订阅

全选清除本页清除全部题录导出标记到"检索档案"

详细简洁

排序：

An efficient point Based Registration of Intra-operative Ultrasound images with MR images for computation of brain shift;a Phantom Study

An efficient Point Based Registration of Intra-operative Ult...

引用

33rd Annual International Conference of the IEEE Engineering-in-Medicine-and-Biology-Society (EMBS)

作者： Farnia, Parastoo Ahmadian, Alireza Khoshnevisan, Alireza Jaberzadeh, AmirHossein Serej, Nasim Dadashi Kazerooni, Anahita F. Univ Tehran Med Sci Dept Biomed Syst & Med Phys Tehran Iran Univ Tehran Med Sci Res Ctr Sci & Technol Med RCSTIM Tehran Iran Univ Tehran Med Sci Imam Hosp Dept Neurosurg Tehran 14174 Iran Univ Tehran Med Sci Brain & Spinal Injuries Repair Res Ctr BASIR Tehran 14174 Iran

ISBN: (纸本)9781424441228

Intra-operative brain deformation (brain shift) limits the accuracy of image-guided neuro-surgery systems. Ultrasound imaging as a simple, fast and being real time has become an alternative to MR imaging which is an expensive system for brain shift calculation. The main challenges due to speckle noise and artifacts in US images, is to perform an accurate and fast registration of Us images with pre-operative MR images. In this paper an efficient point based registration method based on the alignment of probability density functions called Coherent point Drift (CPD) is implemented and compared to the conventional ICP method. To perform this, a brain phantom that allows simulating the brain deformation is made. As the results of our phantom study confirm the CPD method clearly outperforms the ICP algorithm for brain shift calculation. Also the result proves that using intra-operative US has led to recover almost 80% of displacement in the region of interest.

关键词： Electron tubes iterative closest point algorithm MR image MR imaging Magnetic resonance imaging Phantoms Ultrasonic imaging biomedical MRI biomedical ultrasonics brain brain shift calculation coherent point drift density functional theory image artifact i

来源：评论

学校读者我要写书评

暂无评论

The Application of iterative closest point (ICP) Registration to Improve 3D Terrain Mapping Estimates Using the FLASH 3D LADAR System

The Application of Iterative Closest Point (ICP) Registratio...

引用

Conference on Laser Radar Technology and Applications XV

作者： Woods, Jack Armstrong, Ernest E. Armbruster, Walter Richmond, Richard AFRL RYJM Wright Patterson AFB OH 45433 USA Res Inst Optron & Pattern Recognit FGAN FOM D-76275 Ettlingen Germany ITT Informat Sys Beavercreek OH 45431 USA

ISBN: (纸本)9780819481481

The primary purpose of this research was to develop an effective means of creating a 3D terrain map image (point-cloud) in GPS denied regions from a sequence of co-bore sighted visible and 3D LIDAR images. Both the visible and 3D LADAR cameras were hard mounted to a vehicle. The vehicle was then driven around the streets of an abandoned village used as a training facility by the German Army and imagery was collected. The visible and 3D LADAR images were then fused and 3D registration performed using a variation of the iterative closest point (ICP) algorithm. The ICP algorithm is widely used for various spatial and geometric alignment of 3D imagery producing a set of rotation and translation transformations between two 3D images. ICP rotation and translation information obtain from registering the fused visible and 3D LADAR imagery was then used to calculate the x-y plane, range and intensity (xyzi) coordinates of various structures (building, vehicles, trees etc.) along the driven path. The xyzi coordinates information was then combined to create a 3D terrain map (point-cloud). In this paper, we describe the development and application of 3D imaging techniques (most specifically the ICP algorithm) used to improve spatial, range and intensity estimates of imagery collected during urban terrain mapping using a co-bore sighted, commercially available digital video camera with focal plan of 640x480 pixels and a 3D FLASH LADAR. Various representations of the reconstructed point-clouds for the drive through data will also be presented.

关键词： FLASH 3D LADAR iterative closest point algorithm terrain mapping

来源：评论

学校读者我要写书评

暂无评论

Inverse Composition Discriminative Optimization for point Cloud Registration 31

Inverse Composition Discriminative Optimization for Point Cl...

引用

31st IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

作者： Vongkulbhisal, Jayakorn Ugalde, Benat Irastorza De la Torre, Fernando Costeira, Joao P. Univ Lisbon ISR IST Lisbon Portugal Carnegie Mellon Univ Pittsburgh PA 15213 USA Facebook Inc Menlo Pk CA USA

ISBN: (纸本)9781538664209

Rigid point Cloud Registration (PCReg) refers to the problem of finding the rigid transformation between two sets of point clouds. This problem is particularly important due to the advances in new 3D sensing hardware, and it is challenging because neither the correspondence nor the transformation parameters are known. Traditional local PCReg methods (e.g., ICP) rely on local optimization algorithms, which can get trapped in bad local minima in the presence of noise, outliers, bad initializations, etc. To alleviate these issues, this paper proposes Inverse Composition Discriminative Optimization (ICDO), an extension of Discriminative Optimization (DO), which learns a sequence of update steps from synthetic training data that search the parameter space for an improved solution. Unlike DO, ICDO is object-independent and generalizes even to unseen shapes. We evaluated ICDO on both synthetic and real data, and show that ICDO can match the speed and outperform the accuracy of state-of-the-art PCReg algorithms.

关键词： Three-dimensional displays Shape Optimization Integrated circuits Training data Annealing iterative closest point algorithm

来源：评论

学校读者我要写书评

暂无评论

EOE: Expected Overlap Estimation over Unstructured point Cloud Data 6

EOE: Expected Overlap Estimation over Unstructured Point Clo...

引用

6th International Conference on 3D Vision (3DV)

作者： Eckart, Benjamin Kim, Kihwan Kautz, Jan NVIDIA Res Santa Clara CA 95051 USA

ISBN: (纸本)9781538684252

We present an iterative overlap estimation technique to augment existing point cloud registration algorithms that can achieve high performance in difficult real-world situations where large pose displacement and non-overlapping geometry would otherwise cause traditional methods to fail. Our approach estimates overlapping regions through an iterative Expectation Maximization procedure that encodes the sensor field-of-view into the registration process. The proposed technique, Expected Overlap Estimation (EOE), is derived from the observation that differences in field-of-view violate the iid assumption implicitly held by all maximum likelihood based registration techniques. We demonstrate how our approach can augment many popular registration methods with minimal computational overhead. Through experimentation on both synthetic and real-world datasets, we find that adding an explicit overlap estimation step can aid robust outlier handling and increase the accuracy of both ICP-based and GMM-based registration methods, especially in large unstructured domains and where the amount of overlap between point clouds is very small.

关键词： Three-dimensional displays Estimation iterative closest point algorithm Geometry Data models Two dimensional displays

来源：评论

学校读者我要写书评

暂无评论

3D point Cloud Registration for Localization using a Deep Neural Network Auto-Encoder 30

3D Point Cloud Registration for Localization using a Deep Ne...

引用

30th IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

作者： Elbaz, Gil Avraham, Tamar Fischer, Anath Technion Israel Inst Technol Haifa Israel

ISBN: (纸本)9781538604571

We present an algorithm for registration between a large-scale point cloud and a close-proximity scanned point cloud, providing a localization solution that is fully independent of prior information about the initial positions of the two point cloud coordinate systems. The algorithm, denoted LORAX, selects super-points-local subsets of points-and describes the geometric structure of each with a low-dimensional descriptor. These descriptors are then used to infer potential matching regions for an efficient coarse registration process, followed by a fine-tuning stage. The set of super-points is selected by covering the point clouds with overlapping spheres, and then filtering out those of low-quality or nonsalient regions. The descriptors are computed using state-of-the-art unsupervised machine learning, utilizing the technology of deep neural network based auto-encoders. This novel framework provides a strong alternative to the common practice of using manually designed key-point descriptors for coarse point cloud registration. Utilizing super-points instead of key-points allows the available geometrical data to be better exploited to find the correct transformation. Encoding local 3D geometric structures using a deep neural network auto-encoder instead of traditional descriptors continues the trend seen in other computer vision applications and indeed leads to superior results. The algorithm is tested on challenging point cloud registration datasets, and its advantages over previous approaches as well as its robustness to density changes, noise and missing data are shown.

关键词： Three-dimensional displays Neural networks algorithm design and analysis Two dimensional displays iterative closest point algorithm Computer vision Robustness

来源：评论

学校读者我要写书评

暂无评论

Real-time 3D Reconstruction Using a Combination of point-based and Volumetric Fusion

Real-time 3D Reconstruction Using a Combination of Point-bas...

引用

25th IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Xia, Zhengyu Kim, Joohee Park, Young Soo IIT Chicago IL 60616 USA Argonne Natl Lab Argonne IL 60439 USA

ISBN: (纸本)9781538680940

Real-time 3D reconstruction using low-cost commodity sensors like Kinect or Xtion has been successfully applied in a wide range of fields like augmented reality, robotic teleoperation, and medical diagnosis. Due to the assumption of static scene, popular 3D reconstruction technologies such as KinectFusion and KinFu, find truthful reconstruction with fast motion camera or segmenting a moving object to be a challenge. In this paper, we propose a weighted iterative closest point (ICP) algorithm that uses both depth and RGB information to enhance the stability of camera tracking. Additionally, a GPU-based region growing method that combines depth, normal and intensity level as similarity criteria, is also applied to segment foreground moving objects accurately. For real-time processing and GPU memory efficiency, we also design a combination of point-based and volumetric representation to reconstruct moving objects and static scene, respectively. Both qualitative and quantitative results show that our proposed method improves real-time 3D reconstruction on the performance of camera tracking and segmentation of moving objects with reduced computational complexity.

关键词： Cameras Three-dimensional displays Pose estimation Sensors Real-time systems iterative closest point algorithm Systematics

来源：评论

学校读者我要写书评

暂无评论

point Cloud Registration using Congruent Pyramids

Point Cloud Registration using Congruent Pyramids

引用

IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Krishnan, Aravindhan K. Saripalli, Srikanth Arizona State Univ Sch Earth & Space Explorat Tempe AZ 85287 USA

ISBN: (纸本)9781479969340

present a method to compute an initial alignment for pairwise registration of point clouds. This method uses the properties of a rigid body transformation-the ratio of lengths is preserved, the euclidean distance between points is preserved-to find congruent pyramids in two point clouds. The corresponding vertices of the congruent pyramids are used to derive a closed form solution for initial alignment. The alignment is refined further using the iterative closest point algorithm. We validate the method on challenging datasets which include airborne LIDAR, outdoor, and indoor-having initial offsets and varying densities.

关键词： Closed-form solutions Entropy Equations iterative closest point algorithm Laser radar Surfaces Three-dimensional displays

来源：评论

学校读者我要写书评

暂无评论

Color point Cloud Registration with 4D ICP algorithm

Color Point Cloud Registration with 4D ICP Algorithm

引用

IEEE International Conference on Robotics and Automation (ICRA)

作者： Men, Hao Gebre, Biruk Pochiraju, Kishore Stevens Inst Technol Dept Mech Engn Hoboken NJ 07030 USA

ISBN: (纸本)9781612843858

This paper presents methodologies to accelerate the registration of 3D point cloud segments by using hue data from the associated imagery. The proposed variant of the iterative closest point (ICP) algorithm combines both normalized point range data and weighted hue value calculated from RGB data of an image registered 3D point cloud. A k-d tree based nearest neighbor search is used to associated common points in {x, y, z, hue} 4D space. The unknown rigid translation and rotation matrix required for registration is iteratively solved using Singular Value Decomposition (SVD) method. A mobile robot mounted scanner was used to generate color point cloud segments over a large area. The 4D ICP registration has been compared with typical 3D ICP and numerical results on the generated map segments shows that the 4D method resolves ambiguity in registration and converges faster than the 3D ICP.

关键词： Cameras Computational modeling Data models Image color analysis iterative closest point algorithm Laser radar Three dimensional displays

来源：评论

学校读者我要写书评

暂无评论

NRGA Gravitational Approach for Non-Rigid point Set Registration 6

NRGA Gravitational Approach for Non-Rigid Point Set Registra...

引用

6th International Conference on 3D Vision (3DV)

作者： Ali, Sk Aziz Golyanik, Vladislav Stricker, Didier Univ Kaiserslautern Kaiserslautern Germany German Res Ctr Artificial Intelligence DFKI GmbH Kaiserslautern Germany

ISBN: (纸本)9781538684252

Recovery of correspondences between point sets which differ by some non-rigid transformation is an ill-posed problem. Many existing methods underperform on noisy or corrupted input data. In this study, a novel physics-based approach - Non-Rigid Gravitational Approach (NRGA) - for non-rigid point set registration is introduced which is robust to the mentioned artifacts. Thereafter, a distributed N-body simulation and iterative Procrustes alignment nonrigidly transform and register the template point set. Furthermore, in the force field evolution, per-point Gaussian curvature serves as a shape matching descriptor whereas the displacement fields are regularized by coherent collective motion. The optimal alignment is referred to as the state of minimum gravitational potential energy between the point sets. A thorough experimental evaluation and comparison are provided with widely used state-of-the-art methods on 2D and 3D datasets. Experiments show NRGA's robustness against uniform outliers and missing data.

关键词： Gravity Shape Three-dimensional displays iterative closest point algorithm Noise measurement Transforms

来源：评论

学校读者我要写书评

暂无评论

RPM-Net: Robust point Matching using Learned Features

RPM-Net: Robust Point Matching using Learned Features

引用

IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

作者： Yew, Zi Jian Lee, Gim Hee Natl Univ Singapore Dept Comp Sci Singapore Singapore

ISBN: (数字)9781728171685

ISBN: (纸本)9781728171685

iterative closest point (ICP) solves the rigid point cloud registration problem iteratively in two steps: (1) make hard assignments of spatially closest point correspondences, and then (2) find the least-squares rigid transformation. The hard assignments of closest point correspondences based on spatial distances are sensitive to the initial rigid transformation and noisy/outlier points, which often cause ICP to converge to wrong local minima. In this paper, we propose the RPM-Net - a less sensitive to initialization and more robust deep learning-based approach for rigid point cloud registration. To this end, our network uses the differentiable Sinkhorn layer and annealing to get soft assignments of point correspondences from hybrid features learned from both spatial coordinates and local geometry. To further improve registration performance, we introduce a secondary network to predict optimal annealing parameters. Unlike some existing methods, our RPM-Net handles missing correspondences and point clouds with partial visibility. Experimental results show that our RPM-Net achieves state-of-the-art performance compared to existing non-deep learning and recent deep learning methods. Our source code is available at the project website(1).

关键词： Three-dimensional displays iterative closest point algorithm Feature extraction Robustness Annealing Noise measurement Machine learning

来源：评论

学校读者我要写书评

暂无评论

没有更多数据了...

全选清除本页清除全部题录导出标记到“检索档案”

共165页 << < 5 6 7 8 9 10 11 12 13 14 > >>

检索报告对象比较合并检索0

隐藏清空

合并搜索

回到顶部

执行限定条件

内容：

评分：

请选择保存的检索档案：

请选择收藏分类：

订阅名称：

通借通还

温馨提示：

图书名称：

借书校区：

取书校区：

手机号码：

邮箱地址：

一卡通帐号：

电话和邮箱必须正确填写，我们会与您联系确认。

联系人：

所在院系：

联系邮箱：

联系电话：

内蒙古自治区呼和浩特市赛罕区大学西街235号邮编: 010021

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：