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1.
针对大规模点集可能存在噪声、离群点及遮挡等情况,提出一种基于K-means+〖KG-*3〗+的多视图点云配准方法。首先,利用K-means+〖KG-*3〗+算法的随机播种技术对下采样后的多视图点集选取初始化的质心,并根据算法的基本原理完成聚类;其次,将点云数据存入K-D树结构,并利用最近邻搜索算法建立点集间的对应关系,从而提升对应点集的搜索效率;最后,通过迭代最近点算法依照扫描顺序计算各视图聚类得到的点云数据与所有视图间的刚性变换参数,将成对配准造成的误差均匀扩散到每个视图中,直至获得最终配准结果。在Stanford三维点云数据集上进行实验的结果表明,本文提出的方法比近年的部分多视图配准算法具有更高的配准精度及鲁棒性。  相似文献   

2.
This paper presents a novel robust image alignment technique that performs joint geometric and photometric registration in the total least square (TLS) sense. Therefore, we employ the total least square metric instead of the ordinary least square (OLS) metric, which is commonly used in the literature. While the OLS model is sufficient to tackle geometric registration problems, it gives no mutually consistent estimates when dealing with photometric deformations. By introducing a new TLS model, we obtain mutually consistent parameters. Experimental results show that our method is indeed more consistent and accurate in presence of noise compared to existing joint registration algorithms.  相似文献   

3.
The photorealistic modeling of large-scale scenes, such as urban structures, requires a fusion of range sensing technology and traditional digital photography. This paper presents a system that integrates automated 3D-to-3D and 2D-to-3D registration techniques, with multiview geometry for the photorealistic modeling of urban scenes. The 3D range scans are registered using our automated 3D-to-3D registration method that matches 3D features (linear or circular) in the range images. A subset of the 2D photographs are then aligned with the 3D model using our automated 2D-to-3D registration algorithm that matches linear features between the range scans and the photographs. Finally, the 2D photographs are used to generate a second 3D model of the scene that consists of a sparse 3D point cloud, produced by applying a multiview geometry (structure-from-motion) algorithm directly on a sequence of 2D photographs. The last part of this paper introduces a novel algorithm for automatically recovering the rotation, scale, and translation that best aligns the dense and sparse models. This alignment is necessary to enable the photographs to be optimally texture mapped onto the dense model. The contribution of this work is that it merges the benefits of multiview geometry with automated registration of 3D range scans to produce photorealistic models with minimal human interaction. We present results from experiments in large-scale urban scenes.  相似文献   

4.
This paper deals with the registration of geometric shapes. Our primary contribution is the use of a simple and robust shape representation (distance functions) for global-to-local alignment. We propose a rigid-invariant variational framework that can deal as well with local non-rigid transformations. To this end, the registration map consists of a linear motion model and a local deformations field, incrementally recovered. In order to demonstrate the performance of the selected representation a simple criterion is considered, the sum of square differences. Empirical validation and promising results were obtained on examples that exhibit large global motion as well as important local deformations and arbitrary topological changes.  相似文献   

5.
Registration and Analysis of Vascular Images   总被引:1,自引:0,他引:1  
We have developed a method for rigidly aligning images of tubes. This paper presents an evaluation of the consistency of that method for three-dimensional images of human vasculature. Vascular images may contain alignment ambiguities, poorly corresponding vascular networks, and non-rigid deformations, yet the Monte Carlo experiments presented in this paper show that our method registers vascular images with sub-voxel consistency in a matter of seconds. Furthermore, we show that the method's insensitivity to non-rigid deformations enables the localization, quantification, and visualization of those deformations.Our method aligns a source image with a target image by registering a model of the tubes in the source image directly with the target image. Time can be spent to extract an accurate model of the tubes in the source image. Multiple target images can then be registered with that model without additional extractions.Our registration method builds upon the principles of our tubular object segmentation work that combines dynamic-scale central ridge traversal with radius estimation. In particular, our registration method's consistency stems from incorporating multi-scale ridge and radius measures into the model-image match metric. Additionally, the method's speed is due in part to the use of coarse-to-fine optimization strategies that are enabled by measures made during model extraction and by the parameters inherent to the model-image match metric.  相似文献   

6.
Globally Consistent Range Scan Alignment for Environment Mapping   总被引:13,自引:1,他引:12  
A robot exploring an unknown environment may need to build a worldmodel from sensor measurements. In order to integrate all the framesof sensor data, it is essential to align the data properly. Anincremental approach has been typically used in the past, in whicheach local frame of data is aligned to a cumulative global model, andthen merged to the model. Because different parts of the model areupdated independently while there are errors in the registration,such an approach may result in an inconsistent model.In this paper, we study the problem of consistent registration ofmultiple frames of measurements (range scans), together with therelated issues of representation and manipulation of spatialuncertainties. Our approach is to maintain all the local frames ofdata as well as the relative spatial relationships between localframes. These spatial relationships are modeled as random variablesand are derived from matching pairwise scans or from odometry. Thenwe formulate a procedure based on the maximum likelihood criterion tooptimally combine all the spatial relations. Consistency is achievedby using all the spatial relations as constraints to solve for thedata frame poses simultaneously. Experiments with both simulated andreal data will be presented.  相似文献   

7.
为了更好地进行图像弹性点的配准,提出了一种利用Hausdorff距离测度的弹性点配准方法。该方法以B样条为弹性形变模型,并具有较强的抵御杂点影响的能力。在此基础上又提出了序贯更新策略,即通过将源图像和控制点网格进行分块的方法来序贯更新弹性配准参数,从而进一步提高了算法的运算速度。为验证该方法的配准效果,采用该方法进行了合成图像、手写字体和脑部MRI图像的弹性配准实验。实验结果表明,该方法在基于特征的弹性配准应用中具有较好的使用效果。  相似文献   

8.
We present a method for producing dense active appearance models (AAMs), suitable for video-realistic synthesis. To this end we estimate a joint alignment of all training images using a set of pairwise registrations and ensure that these pairwise registrations are only calculated between similar images. This is achieved by defining a graph on the image set whose edge weights correspond to registration errors and computing a bounded diameter minimum spanning tree. Dense optical flow is used to compute pairwise registration and a flow refinement method to align small scale texture is introduced. Further, given the registration of training images, vertices are added to the AAM to minimise the error between the observed flow fields and the flow fields interpolated between the AAM mesh points. We demonstrate a significant improvement in model compactness.  相似文献   

9.
《Graphical Models》2014,76(5):542-553
In this paper we present a novel approach to register multiple scans from a static object. We formulate the registration problem as an optimization of the maps from all other scans to one reference scan where any map between two scans can be represented by the composition of these maps. In this way, all loop closures can be automatically guaranteed as the maps among all scans are globally consistent. Furthermore, to avoid the incorrect correspondences between the points in the scan, we employ a parametric bi-directional approach that generates invertible transformations in pairwise overlapping regions. With the parameter information in use and the consistency taken into consideration, we are able to eliminate the drift that often occurred in multi-view registration process. Our approach is fully automatic and has performed better than existing approaches by various experimental results.  相似文献   

10.
We present an unsupervised method for registering range scans of deforming, articulated shapes. The key idea is to model the motion of the underlying object using a reduced deformable model. We use a linear skinning model for its simplicity and represent the weight functions on a regular grid localized to the surface geometry. This decouples the deformation model from the surface representation and allows us to deal with the severe occlusion and missing data that is inherent in range scan data. We formulate the registration problem using an objective function that enforces close alignment of the 3D data and includes an intuitive notion of joints. This leads to an optimization problem that we solve using an efficient EM-type algorithm. With our algorithm we obtain smooth deformations that accurately register pairs of range scans with significant motion and occlusion. The main advantages of our approach are that it does not require user specified markers, a template, nor manual segmentation of the surface geometry into rigid parts.  相似文献   

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