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Flexible registration method for light-stripe sensors considering sensor misalignments 10

Flexible registration method for light-stripe sensors consid...

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Conference on Optical Measurement Systems for Industrial Inspection X part of the SPIE Optical Metrology Symposium

作者： Gorschenew, W. Kaestner, M. Reithmeier, Eduard Leibniz Univ Hannover Inst Measurement & Automat Control Nienburger Str 17 D-30167 Hannover Germany

ISBN: (纸本)9781510611047;9781510611030

In many application areas such as object reconstruction or quality assurance, it is required to completely or partly measure the shape of an object or at least the cross section of the required object region. For complex geometries, therefore, multiple views are needed to bypass undercuts respectively occlusions. Hence, a multi-sensor measuring system for complex geometries has to consist of multiple light-stripe sensors that are surrounding the measuring object in order to complete the measurements in a prescribed time. The number of sensors depends on the object geometry and dimensions. In order to create a uniform 3D data set from the data of individual sensors, a registration of each individual data set into a common global coordinate system has to be performed. State-of-the-art registration methods for light-stripe sensors use only data from object intersection with the respective laser plane of each sensor. At the same time the assumption is met that all laser planes are coplanar and that there are corresponding points in two data sets. However, this assumption does not represent the real case, because it is nearly impossible to align multiple laser planes in the same plane. For this reason, sensor misalignments are neglected by this assumption. In this work a new registration method for light-stripe sensors is presented that considers sensor misalignments as well as intended sensor displacements and tiltings. The developed method combines 3D pose estimation and triangulated data to properly register the real sensor pose in 3D space.

关键词： 3D registration light-stripe sensors 3D pose estimation icp algorithm rigid body transformation

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The Application of Chaotic BP Neural Network in Underwater Terrain matching navigation

The Application of Chaotic BP Neural Network in Underwater T...

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21st Chinese Control and Decision Conference

作者： Zhang Tao Xu Xiao-su Southeast Univ Dept Instrument Sci & Engn Nanjing 210096 Peoples R China

ISBN: (纸本)9781424427239

As the traditional icp algorithm is liable to get local minimization problem, a chaotic BP neural network is presented in the icp algorithm. In the algorithm, a searching area of real position was plotted centering on the indication of refer navigation system, then terrain altitude data was extracted from refer terrain map. These terrain data, along with corresponding position coordinates, were defined as several patterns and used to train BP network. The network can recognizes certain pattern class with measured water-depth data to determine vehicle's location. However, there are drawbacks of local minimization problem and slow rapidity of convergence in BP network, so improved ways were put forward. The improvement includes replacing common motivating function with chaotic motivating function for and determination of neural network's weights using chaotic search. The experimental results reveal that results of terrain matching can be improved, and matching failure caused by local convergence is overcome to a certain extent.

关键词： terrain matching icp algorithm BP neural networks chaotic motivating function

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Application of Neighborhood Feature in Point Clouds Registration

Application of Neighborhood Feature in Point Clouds Registra...

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International Conference on Computer Science and Network Technology (ICCSNT)

作者： He Yong-Xing Ou Xin-Liang Kuang Xiao-Lan Hunan Univ Technol Coll Comp Commun Zhuzhou 412008 Peoples R China Changsha Univ Dept Comp Sci & Technol Changsha 410003 Hunan Peoples R China Changsha Commerce & Tourism Coll Dept Comp Sci & Technol Changsha 412003 Hunan Peoples R China

ISBN: (纸本)9781457715846

A point clouds registration method based on the invariant features of neighborhood points is proposed. Firstly, the target point set are weighted. Secondly, all the corresponding point-pairs are searched by comparing the feature value and then the preliminary registration is completed. Finally, to register accurately by using the icp algorithm, this has improved the invariant feature. Experiments indicate the good results of the preliminary registration and the better results of the fine registration, which have met the requirement of registering point clouds from different viewpoints.

关键词： Features of neighborhood icp algorithm Point clouds Registration

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Combining ElasticFusion with PSPNet for RGB-D based Indoor Semantic Mapping

Combining ElasticFusion with PSPNet for RGB-D based Indoor S...

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Chinese Automation Congress (CAC)

作者： Wang, Weiqi Yang, Jian You, Xiong Zhengzhou Inst Surveying & Mapping Zhengzhou Henan Peoples R China

ISBN: (纸本)9781728113128

Semantic segmentation has been a research focus of scene parsing and robotic manipulation. And increasing efforts are being made to empower geometry-solely robotic mapping with semantic sensing ability in complex spatial cognition tasks, the so-called semantic mapping. However, semantic mapping has not yet fully exploited the state-of-theart of semantic segmentation and suffered limitations of application scenario, number of object category and accuracy of object detection. Towards a robust semantic mapping solution, we propose a RGB-D based fusion method that combines an improved ElasticFusion with PSPNet. PSPNet has the potential for breaking restrictions of limited object category in semantic segmentation of RGB images. As for map rendering, the improved ElasticFusion algorithm is validated for its robust performance in indoor scenes in terms of overall model accuracy and integral object shape geometry. Based on the two aforementioned modules, we fuses the semantic images and the depth images to generate 3D point cloud with semantic information. Experiments on the ICL-NUIM datasets have proven the feasibility of the proposed method.

关键词： semantic mapping icp algorithm ElasticFusion

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TOWARDS RECONSTRUCTING A DORIC COLUMN IN A VIRTUAL CONSTRUCTION SITE

TOWARDS RECONSTRUCTING A DORIC COLUMN IN A VIRTUAL CONSTRUCT...

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Conference on 3D Virtual Reconstruction and Visualization of Complex Architectures

作者： Bartzis, D. Natl Tech Univ Athens Sch Architecture Patision Str 42 GR-10682 Athens Greece

This paper deals with the 3D reconstruction of ancient Greek architectural members, especially with the element of the Doric column. The case study for this project is the Choragic monument of Nicias on the South Slope of the Athenian Acropolis, from which a column drum, two capitals and smaller fragments are preserved. The first goal of this paper is to present some benefits of using 3D reconstruction methods not only in documentation but also in understanding of ancient Greek architectural members. The second goal is to take advantage of the produced point clouds. By using the Cloud Compare software, comparisons are made between the actual architectural members and an "ideal" point cloud of the whole column in its original form. Seeking for probable overlaps between the two point clouds could assist in estimating the original position of each member/fragment on the column. This method is expanded with more comparisons between the reference column model and other members/fragments around the Acropolis, which may have not yet been ascribed to the monument of Nicias.

关键词： Doric order Doric column architectural member 3D reconstruction point clouds comparison icp algorithm

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Robot Localization Using Laser Positioning of Reflectors Based on icp

Robot Localization Using Laser Positioning of Reflectors Bas...

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第33届中国控制与决策会议

作者： Jingge Yu Anwen Shen Xin Luo Tianzouzi Xiao School of Artificial Intelligence and Automation Huazhong University of Science and Technology

In this paper,the global localization for a mobile robot in the environment with reflectors arran ged in advance is *** robot is equipped with a laser that allows to acquire the range and bearing information of the robot with respect to *** reflector matching,the global pose of the robot can be calculated by localization *** on the localization method,a novel laser positioning method based on icp(Iterative Nearest Point) is proposed,which realizes global localizations by constructing the rigid transformation between reflector sets for two continuous scanning *** addition,compared with the original icp algorithm that dealing with point cloud sets,the proposed method has less computation and needs no *** implementation process of the proposed method is derived,and the proposed method is compared with the widely used trilateral localization *** results show that our method has higher accuracy and better stability than trilateral positioning method.

关键词： global localization laser reflectors icp algorithm trilateral positioning

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A two-dimensional point cloud matching method based on icp improvement

A two-dimensional point cloud matching method based on ICP i...

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第十一届中国卫星导航年会

作者： Huchao Xu Letao Zhou Yinghao Zhao Zheng Yuan Faculty of Geosciences and Environmental Engineering Southwest Jiaotong University

The indoor map is the basis of indoor navigation and positioning. The core problem of indoor map construction by using two-dimensional lidar is to solve the matching problem between different point cl

关键词： point cloud matching icp algorithm lidar indoor map construction

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3D Model Registration Based on Feature Extraction

3D Model Registration Based on Feature Extraction

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International Conference on Materials and Manufacturing (ICMM 2011)

作者： Zhu, Jiang Takekuma, Yuichi Tanaka, Tomohisa Saito, Yoshio Tokyo Inst Technol Dept Mech & Control Engn Meguro Ku Tokyo 1528552 Japan

ISBN: (纸本)9783037852019

Currently, design and processing of complicated model are enabled by the progress of the CAD/CAM system. In shape measurement, high precision measurement is performed using CMM. In order to evaluate the machined part, the designed model made by CAD system the point cloud data provided by the measurement system are analyzed and compared. Usually, the designed CAD model and measured point cloud data are made in the different coordinate systems, it is necessary to register those models in the same coordinate system for evaluation. In this research, a 3D model registration method based on feature extraction and iterative closest point (icp) algorithm is proposed. It could efficiently and accurately register two models in different coordinate systems, and effectively avoid the problem of localized solution.

关键词： CAD Model Feature extraction icp algorithm Model Registration

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Registration of large data sets for multimodal inspection

Registration of large data sets for multimodal inspection

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Conference on Applications of Digital Image Processing XXIX

作者： Vedula, V. S. Venumadhav George, Sheri GE Global Res Ctr Ind Imaging & Modeling Lab Bangalore 560066 Karnataka India

ISBN: (纸本)0819463914

Registration plays a key role in multimodal data fusion to extract synergistic information from multiple non-destructive evaluation (NDE) sources. One of the common techniques for registration of point datasets is the Iterative Closest Point (icp) algorithm. Generally, modem day NDE techniques generate large datasets and conventional icp algorithm requires huge amount of time to register datasets to the desired accuracy. In this paper, we present algorithms to aid in the registration of large 3D NDE data sets in less time with the required accuracy. Various methods of coarse registration of data, partial registration and data reduction are used to realize this. These techniques have been used in registration and it is shown that registration can be accomplished to the desired accuracy with more than 90% reduction in time as compared to conventional icp algorithm. Volumes of interest (VOI) can be defined on the data sets and merged together so that only the features of interest are used in the registration. The proposed algorithm also provides capability for eliminating noise in the data sets. Registration of Computed Tomography (CT) Image data, Coordinate Measuring Machine (CMM) Inspection data and CAD model has been discussed in the present work. The algorithm is generic in nature and can be applied to any other NDE inspection data.

关键词： registration icp algorithm CMM data CT data VOI CAD Model

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Automatic strategy for extraction of anthropometric measurements for the diagnostic and evaluation of deformational plagiocephaly from infant's models

Automatic strategy for extraction of anthropometric measurem...

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Conference on Medical Imaging - Computer-Aided Diagnosis

作者： Oliveira, Bruno Torres, Helena R. Veloso, Fernando Vilhena, Estela Rodrigues, Nuno F. Fonseca, Jaime C. Morais, Pedro Vilaca, Joao L. 2Ai Polytech Inst Cavado & Ave Barcelos Portugal Univ Minho Sch Engn Algoritmi Ctr Guimaraes Portugal

ISBN: (数字)9781510625488

ISBN: (纸本)9781510625488

Deformational Plagiocephaly (DP) refers to an asymmetrical distortion of an infant's skull resulting from external forces applied over time. The diagnosis of this condition is performed using asymmetry indexes that are estimated from specific anatomical landmarks, whose are manually defined on head models acquired using laser scans. However, this manual identification is susceptible to intra-/inter-observer variability, being also time-consuming. Therefore, automatic strategies for the identification of the landmarks and, consequently, extraction of asymmetry indexes, are claimed. A novel pipeline to automatically identify these landmarks on 3D head models and to estimate the relevant cranial asymmetry indexes is proposed. Thus, a template database is created and then aligned with the unlabelled patient through an iterative closest point (icp) strategy. Here, an initial rigid alignment followed by an affine one are applied to remove global misalignments between each template and the patient. Next, a non-rigid alignment is used to deform the template information to the patient-specific shape. The final position of each landmark is computed as a local weight average of all candidate results. From the identified landmarks, a head's coordinate system is automatically estimated and later used to estimate cranial asymmetry indexes. The proposed framework was evaluated in 15 synthetic infant head's model. Overall, the results demonstrated the accuracy of the identification strategy, with a mean average distance of 2.8 +/- 0.6 mm between the identified landmarks and the ground-truth. Moreover, for the estimation of cranial asymmetry indexes, a performance comparable to the inter-observer variability was achieved.

关键词： icp algorithm landmark detection anthropometric measurements infant's head models deformational plagiocephaly

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