改进的三维模型形状分布检索算法

针对传统D1距离形状分布函数获取采样点计算复杂、模型内容描述不充分和检索速率低下等问题提出了一种改进方法。该方法的关键点是：首先采用平移和缩放对模型进行标准化处理,用于减少面片之间的差异,使得采样点均匀地落在模型的表面;其次采用三角面片的索引号进行随机数的生成,并且利用三角面片的重心和质心进行有效的计算,以便用于缩短模型的处理时间和提高检索速率。利用普林斯顿大学三维模型数据库中的部分模型作为实验数据,实现结果表明：改进的方法不会降低模型的检索性能,并有效地减少了模型查询和处理时间。     

互信息启发的相似度组合图像检索算法

图像的视觉特征与用户描述之间的差距一直是影响基于内容的图像检索准确度的最主要因素。对多种相似度进行组合来检索图像是近几年图像检索领域涌现出的一个研究热点,也是缩小这种差距的一种有效途径。如何选择更好的组合方法则是该领域很多研究者关注的核心问题。提出一种新的相似度组合算法。该算法基于互信息度量相对熵的原理,计算连续变量相似度与离散变量相似性之间的相关性,对多种相似度进行选择,以“和规则”组合相似度。在公用数据集上进行检索实验,该算法优于当前其他的“和规则”下的组合方法。     

A survey of content based 3D shape retrieval methods

Recent developments in techniques for modeling, digitizing and visualizing 3D shapes has led to an explosion in the number of available 3D models on the Internet and in domain-specific databases. This has led to the development of 3D shape retrieval systems that, given a query object, retrieve similar 3D objects. For visualization, 3D shapes are often represented as a surface, in particular polygonal meshes, for example in VRML format. Often these models contain holes, intersecting polygons, are not manifold, and do not enclose a volume unambiguously. On the contrary, 3D volume models, such as solid models produced by CAD systems, or voxels models, enclose a volume properly. This paper surveys the literature on methods for content based 3D retrieval, taking into account the applicability to surface models as well as to volume models. The methods are evaluated with respect to several requirements of content based 3D shape retrieval, such as: (1) shape representation requirements, (2) properties of dissimilarity measures, (3) efficiency, (4) discrimination abilities, (5) ability to perform partial matching, (6) robustness, and (7) necessity of pose normalization. Finally, the advantages and limitations of the several approaches in content based 3D shape retrieval are discussed.

Efficient 3D shape matching and retrieval using a concrete radialized spherical projection representation

We present a 3D shape retrieval methodology based on the theory of spherical harmonics. Using properties of spherical harmonics, scaling and axial flipping invariance is achieved. Rotation normalization is performed by employing the continuous principal component analysis along with a novel approach which applies PCA on the face normals of the model. The 3D model is decomposed into a set of spherical functions which represents not only the intersections of the corresponding surface with rays emanating from the origin but also points in the direction of each ray which are closer to the origin than the furthest intersection point. The superior performance of the proposed methodology is demonstrated through a comparison against state-of-the-art approaches on standard databases.     

基于形状熵的图像检索方法*

提出了一种新的相似性图像检索方法.该方法利用信息熵理论,对图像的形状特征进行描述.首先分割图像,把一幅图像划分为若干子区域,抽取图像的主要形状并统计其所含的角度信息;再利用信息熵计算图像之间的形状互信息.用该方法对不同类型图像进行实验,结果表明,与其他方法相比其具有更好的效果,抗噪性强,也更稳定.     

2D and 3D shape retrieval using skeleton filling rate

As an increasing number of digital images are generated, a demand for an efficient and effective image retrieval mechanisms grows. In this work, we present a new skeleton-based algorithm for 2D and 3D shape retrieval. The algorithm starts by drawing circles (spheres for 3D) of increasing radius around skeletons. Since each skeleton corresponds to the center of a maximally inscribed circle (sphere), this process results in circles (spheres) that are partially inside the shape. Computing the ratio between pixels that lie within the shape and the total number of pixels allows us to distinguish shapes with similar skeletons. Experimental evaluation of the proposed approach including a comprehensive comparison with the previous techniques demonstrates both effectiveness and robustness of our algorithm for shape retrieval using several 2D and 3D datasets.     

基于核线性分类分析的三维模型检索算法

为提高检索精确度,提出了一种利用核线性分类分析来对模型特征进行优化的新方法。其主要思想是通过满足Mercer条件的非线性映射将低维空间下线性不可分的样本映射到高维空间,在高维空间中利用线性分类分析将原有的三维模型特征投影到特定的子空间。该方法能够在保持类间距离基础上得到具有鉴别信息的低维特征用于三维模型检索。实验结果表明,核线性分类分析方法速度较快,可在秒级完成三维特征优化,同时优化特征在本文测试数据集上可平均提高搜索准确度15%。     

Progressive 3D shape segmentation using online learning

In this article, we propose a progressive 3D shape segmentation method, which allows users to guide the segmentation with their interactions, and does segmentation gradually driven by their intents. More precisely, we establish an online framework for interactive 3D shape segmentation, without any boring collection preparation or training stages. That is, users can collect the 3D shapes while segment them, and the segmentation will become more and more precise as the accumulation of the shapes.Our framework uses Online Multi-Class LPBoost (OMCLP) to train/update a segmentation model progressively, which includes several Online Random forests (ORFs) as the weak learners. Then, it performs graph cuts optimization to segment the 3D shape by using the trained/updated segmentation model as the optimal data term. There exist three features of our framework. Firstly, the segmentation model can be trained gradually during the collection of the shapes. Secondly, the segmentation results can be refined progressively until users’ requirements are met. Thirdly, the segmentation model can be updated incrementally without retraining all shapes when users add new shapes. Experimental results demonstrate the effectiveness of our approach.     

模型显著域上的形状调控和处理

基于3维数字模型的显著性度量和显著域处理技术,提出一种模型显著域上的形状调控和处理方法。该方法首先基于曲面上采样顶点处局部投影高度的Gaussian加权平均双边滤波定义数字模型的表面显著性;然后利用定义在模型显著域上的形状调控函数——显著域低通形状调控函数、显著域高通形状调控函数和显著域增强形状调控函数,使模型的显著特征得到有效抑制、提升和增强,实现了针对模型表面显著特征的形状调控和处理。实验结果表明,该方法能够方便快速地实现3维数字模型的不同形状造型效果。     

基于相似性序列分析的三维模型检索性能评价

普林斯顿形状基准数据库已经成为当前三维模型检索研究人员使用最为广泛的基准数据库之一。但是该基准数据库存在着一个重要的缺陷,那便是模型类别之间的相似性没有被考虑,这导致在对检索结果进行性能评价时出现与人类直观感觉不一致的结论。为了克服这个缺陷,提出了一种新的基准数据库分类方案,并且在此基础上提出了一种基于相似性序列分析的检索性能评估方法。     

PCA-based 3D shape reconstruction of human foot using multiple viewpoint cameras

This paper describes a multiple camera-based method to reconstruct the 3D shape of a human foot. From a foot database, an initial 3D model of the foot represented by a cloud of points is built. The shape parameters, which can characterize more than 92% of a foot, are defined by using the principal component analysis method. Then, using ＂active shape models＂, the initial 3D model is adapted to the real foot captured in multiple images by applying some constraints （edge points＇ distance and color variance）. We insist here on the experiment part where we demonstrate the efficiency of the proposed method on a plastic foot model, and also on real human feet with various shapes. We propose and compare different ways of texturing the foot which is needed for reconstruction. We present an experiment performed on the plastic foot model and on human feet and propose two different ways to improve the final 3D shapers accuracy according to the previous experiments＇ results. The first improvement proposed is the densification of the cloud of points used to represent the initial model and the foot database. The second improvement concerns the projected patterns used to texture the foot. We conclude by showing the obtained results for a human foot with the average computed shape error being only 1.06 mm.     

使用形状变化描述三维模型

针对三维模型检索中的形状特征提取问题,提出利用三维模型自身形状变化信息构造形状特征描述符的方法.首先选择一组等间距互相平行的平面切割三维模型,得到三维模型的切片集合;然后定义相邻切片的 差来描述切片间的形状变化,并通过所有相邻切片间的差值来反映三维模型自身的形状变化,以此作为三维模型的形状特征描述符.该方法与三维模型的旋转、平移无关,同时不依赖于模型的点云分布,并且精简模型三角面片对算法的影响较小.实验结果验证了该方法的有效性.     

3D shape acquisition and integral compact representation using optical scanning and enhanced shape parameterization

An efficient computational methodology for shape acquisition, processing and representation is developed. It includes 3D computer vision by applying triangulation and stereo-photogrammetry for high-accuracy 3D shape acquisition. Resulting huge 3D point clouds are successively parameterized into mathematical surfaces to provide for compact data-set representation, yet capturing local details sufficiently. B-spline surfaces are employed as parametric entities in fitting to point clouds resulting from optical 3D scanning. Beyond the linear best-fitting algorithm with control points as fitting variables, an enhanced non-linear procedure is developed. The set of best fitting variables in minimizing the approximation error norm between the parametric surface and the 3D cloud includes the control points coordinates. However, they are augmented by the set of position parameter values which identify the respectively closest matching points on the surface for the points in the cloud. The developed algorithm is demonstrated to be efficient on demanding test cases which encompass sharp edges and slope discontinuities originating from physical damage of the 3D objects or shape complexity.