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Surface matching for high-accuracy registration of the lateral skull base

INTERNATIONAL JOURNAL OF COMPUTER ASSISTED RADIOLOGY AND SURGERY 2016年第11期11卷 2097-2103页

作者： Zhou, Chaozheng Anschuetz, Lukas Weder, Stefan Xie, Le Caversaccio, Marco Weber, Stefan Williamson, Tom Univ Bern ARTORG Ctr Biomed Engn Bern Switzerland Univ Hosp Bern Dept ENT Head & Neck Surg Bern Switzerland Shanghai Jiao Tong Univ Inst Forming Technol & Equipment Shanghai Peoples R China

The accuracy achievable when utilizing image guidance depends to a large extent on the accuracy with which the patient can be registered to preoperative image data. This work proposes a method for the registration of the temporal bone based on surface matching and investigates the achievable accuracy of the technique. Fourteen human temporal bones were utilized for evaluation;incisions were made, fiducial screws were implanted to act as a ground truth, and imaging was performed. The positions of the fiducials and surface of the mastoid were extracted from image data and reference positions defined at the round window and the mastoid surface. The surface of the bone was then digitized using a tracked pointer within the region exposed by the incisions and the physical and image point clouds registered, with the result compared to the fiducial-based registration. Results of one case were excluded due to a problem with the ground truth registration. In the remaining cases an accuracy of and mm was observed relative to the ground truth at the surface of the mastoid and round window, respectively. A technique for the registration of the temporal bone was proposed, based on surface matching after exposure of the mastoid surface, and evaluated on human temporal bone specimens. The results reveal that high-accuracy patient-to-image registration is possible without the use of fiducial screws.

关键词： Surgical navigation Patient-to-image registration Surface matching icp algorithm

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Alignment of two-dimensional electrophoresis gels

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BIOCHEMICAL AND BIOPHYSICAL RESEARCH COMMUNICATIONS 2007年第2期357卷 427-432页

作者： Shi, Guihua Jiang, Tianzi Zhu, Wanlin Liu, Bing Zhao, Huizhi Chinese Acad Sci Natl Lab Pattern Recognit Inst Automat Beijing 100080 Peoples R China

Two-dimensional electrophoresis is a major separating technique for proteins in proteomics. Alignment of gel images is critical for intra-laboratory or even more difficult inter-laboratory gel comparisons. In the paper, we propose a novel iterative closest point (icp) method for 2D-gel electrophoresis image alignment. The paper seeks to introduce an information theoretic measure as one part of distance metric to gel image alignment. We combine intensity information of spots with geometric information of landmarks by applying information potential idea. The proposed method has been applied to both synthetic and real gel images accessible in public 2D-electrophoresis gel protein databases. The high accuracy and robustness of the algorithm indicate that it is promising for gel image alignment. (c) 2007 Elsevier Inc. All rights reserved.

关键词： 2D-gel electrophoresis image image alignment icp algorithm informational potential

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Geometrically stable tracking for depth images based 3D reconstruction on mobile devices

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ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING 2018年 143卷 222-232页

作者： Liu, Yangdong Gao, Wei Hu, Zhanyi Chinese Acad Sci Inst Automat Natl Lab Pattern Recognit Beijing 100190 Peoples R China Univ Chinese Acad Sci Beijing 100049 Peoples R China

With the development of hardwares such as mobile devices and portable depth cameras, on-line 3D reconstruction on the mobile devices with depth streams as input turns to be possible and promising. Most existing systems use volumetric representation methods to fuse the depth images and use icp algorithm to estimate the poses of cameras. However, icp tracker suffers from large drift in scenes containing insufficient geometric information. To deal with this problem, we propose a stability based sampling method which select different number of point-pairs in different windows according to their geometric stability. In addition, we fuse the icp tracker with the IMU information through an analysis of the condition number. Then we apply the stability based sampling method to the spatially hashed volumetric representation. Qualitative and quantitative evaluations of tracking accuracy and 3D reconstruction results show that our method outperforms the current state-of-the-art systems, especially in scenes lacking sufficient geometric information. In total, our method achieves frame rates 20 Hz on an Apple iPad Air 2 and 200 Hz on a Nvidia GeForce GTX 1060 GPU. (C) 2018 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS). Published by Elsevier B.V. All rights reserved.

关键词： Visual-SLAM Dense mapping icp algorithm Sampling algorithm On-line Mobile device

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A new pose estimation method for non-cooperative spacecraft based on point cloud

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International Journal of Intelligent Computing and Cybernetics 2019年第1期12卷 23-41页

作者： Zhiming Chen Lei Li Yunhua Wu Bing Hua Kang Niu College of Astronautics Nanjing University of Aeronautics and AstronauticsNanjingChina Shanghai Institute of Mechanical and Electrical Engineering ShanghaiChina

Purpose–On-orbitservice technologyis one of the key technologies of space manipulation activities such as spacecraft life extension,fault spacecraft capture,on-orbit debris removal and so *** is known that the failure satellites,space debris and enemy spacecrafts in space are almost all non-cooperative *** accurate pose estimation is critical to spatial operations,but also a recognized technical difficulty because of the undefined prior information of non-cooperative *** the rapid development of laser radar,the application of laser scanning equipment is increasing in the measurement of non-cooperative *** is necessary to research a new pose estimation method for non-cooperative targets based on 3D point *** paper aims to discuss these ***/methodology/approach–In this paper,a method based on the inherent characteristics of a spacecraft is proposed for estimating the pose(position and attitude)of the spatial non-cooperative ***,we need to preprocess the obtained point cloud to reduce noise and improve the quality of ***,according to the features of the satellite,a recognition system used for non-cooperative measurement is *** components which are common in the configuration of satellite are chosen as the recognized ***,based on the identified object,the icp algorithm is used to calculate the pose between two frames of point cloud in different times to finish pose ***–The new method enhances the matching speed and improves the accuracy of pose estimation compared with traditional methods by reducing the number of matching *** recognition of components on non-cooperative spacecraft directly contributes to the space docking,on-orbit capture and relative *** limitations/implications–Limited to the measurement distance of the laser radar,this paper considers the pose estimation for non-cooperative spacecraft in the close *** implications–

关键词： Point cloud Pose estimation icp algorithm Non-cooperative spacecraft RANSAC algorithm

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Study on the Optimization Method of Dynamic Reconstruction of 3D Non-Rigid Image

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RECENT ADVANCES IN ELECTRICAL & ELECTRONIC ENGINEERING 2016年第3期9卷 162-166页

作者： Wang, Chong Li, Ming Qiqihar Univ Coll Comp & Control Engn Qiqihar 518172 Peoples R China

Background: The global registration algorithm is adopted to optimize the icp algorithm, each match point is matched simultaneously for the entire depth image registered with icp, in order to obtain the optimal solution of translation and rotation matrix for images of all perspectives. Methods: In the process of dynamic reconstruction of a three-dimensional (3D) non-rigid image, some image regions overlap, in the traditional 3D non-rigid dynamic image reconstruction method based on FDK, all the overlapping regions are calculated with icp, which greatly increases computational complexity. A dynamic reconstruction optimization method for the 3D non-rigid image is raised based on the global registration, the disadvantages of icp algorithm are analyzed, and the global registration algorithm is adopted to optimize the icp algorithm, each match point is matched simultaneously for the entire depth image registered with icp, in order to obtain the optimal solution of translation and rotation matrix for images of all perspectives. Result: The feature vectors in the process of 3D image reconstruction are classified. The empirical knowledge between the feature vectors and information are utilized to train 3D reconstruction of learning samples. The simulation results show that the method shortens the time of 3D image reconstruction and improves the accuracy of 3D image reconstruction.

关键词： Dynamic optimization reconstruction three-dimensional non-rigid image global registration icp algorithm FDK method

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Localization and mapping in urban area based on 3D point cloud of autonomous vehicles

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Journal of Beijing Institute of Technology 2016年第4期25卷 473-482页

作者：王美玲李玉杨毅朱昊刘彤 Key Laboratory of Intelligent Control and Decision of Complex System School of AutomationBeijing Institute of Technology

In order to meet the application requirements of autonomous vehicles, this paper proposes a simultaneous localization and mapping （SLAM） algorithm, which uses a VoxelGrid filter to down sample the point cloud data, with the combination of iterative closest points （icp） algorithm and Gaussian model for particles updating, the matching between the local map and the global map to quantify particles＇ importance weight. The crude estimation by using icp algorithm can find the high probability area of autonomous vehicles＇ poses, which would decrease particle numbers, increase algorithm speed and restrain particles＇ impoverishment. The calculation of particles＇ importance weight based on matching of attribute between grid maps is simple and practicable. Experiments carried out with the autonomous vehicle platform validate the effectiveness of our approaches.

关键词： simultaneous localization and mapping (SLAM) Rao-Blackwellized particle filter ( RB-PF) VoxelGrid filter icp algorithm Gaussian model urban area

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RESEARCH ON POWER TRANSMISSION CHANNEL CHANGE DETECTION BASED ON MULTI-TEMPORAL POINT CLOUD DATA 5

RESEARCH ON POWER TRANSMISSION CHANNEL CHANGE DETECTION BASE...

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5th International-Society-for-Photogrammetry-and-Remote-Sensing (ISPRS) Geospatial Week (GSW)

作者： Hu, Wei Yang, Guozhu Liu, Ning Liu, Fei Ma, Chuntian Tian, Maojie Hao, Chunting State Grid Elect Power Space Technol Co Ltd Beijing Peoples R China Beijing Univ Civil Engn & Architecture Beijing Peoples R China

Airborne LiDAR can directly obtain 3D information of ground objects. By comparing the multi-temporal LiDAR data, ground objects change information of power transmission channel can be detected, providing data support for transmission line operation and maintenance. In this paper, an improved icp algorithm based on multi-temporal LiDAR point cloud data power transmission channel ground object change detection method is proposed. Firstly, based on the classification of point cloud data, a two-level matching method of multi-temporal point cloud data considering the characteristics of power transmission channel was proposed to achieve accurate registration of point cloud data. Then, change detection and analysis of different types of ground feature point cloud data were carried out through elevation difference. Finally, cluster analysis was carried out on the changed ground feature points to generate multi-temporal relative ratio analysis report. Experimental results show that the proposed method can effectively detect power transmission channel changes.

关键词： icp algorithm Change Detection Point Cloud Registration Multi-temporal Point Cloud

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A coarse registration method of range image based on SIFT

A coarse registration method of range image based on SIFT

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Conference on Electronic Imaging and Multimedia Technology V

作者： Liu, Xiaoli Peng, Xiang Yin, Yongkai Tian, Jindong Li, Ameng Zhao, Xiaobo Shenzhen Univ Inst Optoelect Shenzhen 518060 Peoples R China

ISBN: (纸本)9780819470089

A novel method for the coarse registration of range images is proposed. This approach is based on texture-feature recognition. As the development of optical digitizing technique, it is now able to acquire the range images and associated texture images sequentially or simultaneously. It's possible to identify the range feature points through texture feature points. Scale Invariant Feature Transform (SIFT) is an efficient method for texture feature generation. SIFT transforms texture image into a large collection of local feature vectors, each of which is invariant to image scaling, translation, and rotation. The mismatched correspondence pairs can be discarded using random sample consensus algorithm based on epipolar geometry constraint. We select more than three well-registered texture-feature pairs, with which we could find the associated range-feature pairs of the range images. Initial pose estimation of the two involved range images can be computed by these range pairs, and the fine registration is implemented using iterative closest point (icp) algorithm. Our approach utilizes the texture information to register the range images, leading to a technique that can be automatically performed while the influence of 3D noise can be avoided. The experiment results demonstrate that the proposed approach is efficient and robust for the registration of multiple range images.

关键词： registration SIFT RANSAC epipolar geometry icp algorithm

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Recognition of 3-D Faces with Missing Parts and Line Scratch Removal using New Technique

Recognition of 3-D Faces with Missing Parts and Line Scratch...

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International Conference on Pervasive Computing (icpC)

作者： Pawar, Asmita A. Patil, Nitin N. SESs RC Patel Inst Technol Dept Comp Engn Shirpur MS India

ISBN: (纸本)9781479962723

This paper presents an implementation of face recognition, which is a very important task of human face identification. Line scratch detection in images is a highly challenging situation because of various characteristics of this defect. Few characteristics are considered with the different texture and geometry of images. We propose a useful algorithm for frame-by-frame line scratch detection in face image which deals with 3D approach and a filtering of detection. The temporary filtering algorithm can be used to remove false detection due to thin vertical structures by detecting the scratches on an image. Experimental evaluation can be detecting the lines and scratches on a face image and they used to solve this difficult approach. Our method is used with missing parts in an image. Three-dimensional face recognition is an extended method of facial recognition is considered according with the geometry and texture of a face. It has been elaborated that 3D face recognition methods can provide high accuracy as well as high detection with a comparison of 2D recognition. 3D avoids such mismatch effect of 2D face recognition algorithms. Additionally, most 3D scanners achieve both a 3D mesh and the texture of a face image. This allows combining the output of pure 3D matches with the more traditional algorithms of 2D face recognition, thus producing better performance.

关键词： 3D Images Adaptive detection Face mask Hough transforms icp algorithm Line scratches Missing parts RANSAC SIFT

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Local Structure to Solve the Correspondence Search Problem in a Monocular Pose Estimation Scenario

Local Structure to Solve the Correspondence Search Problem i...

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2nd International Conference on Computer Graphics Theory and Applications/2nd International Conference on Computer Vision Theory and Applications

作者： Chavarria, Marco A. Sommer, Gerald Univ Kiel Cognit Syst Grp D-24098 Kiel Germany

ISBN: (纸本)9783540896814

In this paper we present a new approach that uses local structural information to find correspondences between image and model contour information. For a monocular pose estimation scenario, the pose is computed by our purposed new variant of the icp (iterative closest point) algorithm which combines Euclidean distance with structure. A local representation of 3D free-form contours is used to get the structural information in 3D space and in the image plane. Furthermore, the local structure of free-form contours is combined with local orientation and phase obtained from the monogenic signal. With this combination, we achieve a more robust correspondence search. Our approach was tested on synthetical and real data to compare the convergence and performance of our approach against the classical icp approach.

关键词： Pose estimation icp algorithm monogenic signal

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