3D模型检索技术综述

全面地综述了3D模型检索技术,介绍了3D模型检索界面和一个3D模型检索系统,并对该技术领域的未来发展进行了总结和展望．     

基于内容的三维模型检索综述

对当前基于内容的三维模型检索技术的国际研究现状及进展进行了广泛而深入的综述．探讨和分析了基于内容的三维模型检索技术的系统框架及其关键方法,重点介绍其中的模型坐标标准化、特征提取与索引、相似性匹配、查询方式与用户界面等方面的基本内容,并进行了适当分类．分析总结了现有的基于内容的三维模型检索系统及搜索引擎的典型实例．最后,对现有研究中存在的难点问题及其未来的发展方向进行了展望．     

三维CAD模型局部结构检索属性图算法

由用户交互式地选择欲检索的模型局部结构,并自动生成该局部结构的属性图;然后取出三维CAD模型库中每个待检索模型,根据模型的B-rep表示过滤出其中与欲检索局部结构组成面相似的面,通过删除不相关面,有效地将可能相似的局部结构从待检索模型中分离出来;最后利用图论中二分图最优匹配算法计算出模型中分离出的结构和欲检索局部结构的相似系数,并将该相似系数作为实现模型局部相似性检索的依据.实验表明,该算法能够实现CAD模型局部结构检索,并与人视觉上的相似性判断基本一致.     

三维模型语义检索研究进展

针对近年来三维模型检索研究不只是考虑形状相似性匹配,而更多地关注如何把语义知识应用于检索这一研究新动态,对三维模型语义检索研究现状,包括三维模型知识提取、语义检索中的主动学习机制、三维模型语义检索系统等方面进行总结.在此基础上,对已有研究成果进行比较分析,突出三维模型语义检索取得的进展以及存在的问题.最后,提出三维模型语义检索需要进一步深入研究的方向.     

三维CAD模型检索综述

对三维CAD模型检索研究现状进行了深入和系统的综述。CAD模型检索可划分为两个层次:基于视觉相似性的三维CAD模型检索、面向语义与功能描述的三维CAD模型检索。分别分析了两种检索层次下CAD模型的检索方法。在此基础上总结了三维CAD模型检索评测基准库、评测方法等。最后展望了现有研究中的难点及进一步的研究方向。     

Partial 3D Shape Retrieval by Reeb Pattern Unfolding

This paper presents a novel approach for fast and efficient partial shape retrieval on a collection of 3D shapes. Each shape is represented by a Reeb graph associated with geometrical signatures. Partial similarity between two shapes is evaluated by computing a variant of their maximum common sub-graph.
By investigating Reeb graph theory, we take advantage of its intrinsic properties at two levels. First, we show that the segmentation of a shape by a Reeb graph provides charts with disk or annulus topology only. This topology control enables the computation of concise and efficient sub-part geometrical signatures based on parameterisation techniques. Secondly, we introduce the notion of Reeb pattern on a Reeb graph along with its structural signature. We show this information discards Reeb graph structural distortion and still depicts the topology of the related sub-parts. The number of combinations to evaluate in the matching process is then dramatically reduced by only considering the combinations of topology equivalent Reeb patterns.
The proposed framework is invariant against rigid transformations and robust against non-rigid transformations and surface noise. It queries the collection in interactive time (from 4 to 30 seconds for the largest queries). It outperforms the competing methods of the SHREC 2007 contest in term of NDCG vector and provides, respectively, a gain of 14.1% and 40.9% on the approaches by Biasotti et al. [ BMSF06 ] and Cornea et al. [ CDS*05 ].
As an application, we present an intelligent modelling-by-example system which enables a novice user to rapidly create new 3D shapes by composing shapes of a collection having similar sub-parts.     

Learning Robust Similarity Measures for 3D Partial Shape Retrieval

In this paper, we propose a novel approach to learning robust ground distance functions of the Earth Mover’s distance to make it appropriate for quantifying the partial similarity between two feature-sets. First, we define the ground distance as a monotonic transformation of commonly used feature-to-feature base distance (or similarity) measures, so that in computing the Earth Mover’s distance, the algorithm could better turn its focus on the feature pairs that are correctly matched, while being less affected by irrelevant ones. As a result, the proposed method is especially suited for 3D partial shape retrieval where occlusion and clutter are serious problems. We prove that when the transformation satisfies certain conditions, the metric property of the base distance is sufficient to guarantee the ground distance is a metric (and so is the Earth Mover’s distance), which makes fast shape retrieval on large databases technically possible. Second, we propose a discriminative learning framework to optimize the transformation function based on the real Adaboost algorithm. The optimization is performed in the space of the piecewise constant approximations of the transformation without making any parametric assumption. Finally, extensive experiments on 3D partial shape retrieval convincingly demonstrate the effectiveness of the proposed techniques.     

非刚性三维模型检索特征提取技术研究

三维模型特征描述符是一种简洁且信息量丰富的表示方式.特征提取是许多三维模型分析处理任务的关键步骤.近年来,针对非刚性三维模型特征提取技术的研究引起了人们的广泛关注.本文首先汇总了常用的非刚性三维模型基准数据集和算法评价标准.然后在广泛调研大量文献和最新成果的基础上,将非刚性三维模型特征分为人工设计的特征描述符和基于学习的特征描述符两大类并分别加以介绍.对每类方法所包含的典型算法,尤其是最近几年基于深度学习的特征提取算法的基本思想、优缺点进行了分析、对比和总结.最后进行总结,并对未来可能的发展趋势加以展望.     

A Frequency-Domain Approach to Watermarking 3D Shapes

This paper presents a robust watermarking algorithm with informed detection for 3D polygonal meshes. The algorithm is based on our previous algorithm [ 22 ] that employs mesh‐spectral analysis to modify mesh shapes in their transformed domain. This paper presents extensions to our previous algorithm so that (1) much larger meshes can be watermarked within a reasonable time, and that (2) the watermark is robust against connectivity alteration (e.g., mesh simplification), and that (3) the watermark is robust against attacks that combine similarity transformation with such other attacks as cropping, mesh simplification, and smoothing. Experiment showed that our new watermarks are resistant against mesh simplification and remeshing combined with resection, similarity transformation, and other operations..     

三维形状特征提取技术研究进展

三维形状模型广泛应用于工业设计、教育、生物医药、动画娱乐、文物保护等多个领域中。三维形状模型的特征提取是计算机图形学和模式识别领域的重要问题,近年来受到学者的广泛关注。尤其是具有铰链、关节等的非刚性三维形状通常会发生变形,进一步增加了形状特征提取的难度。主要研究、分析、总结了近几年出现的刚性三维形状和非刚性三维形状的特征提取算法,分析了三维形状特征提取的难点,给出了三维形状特征提取的发展进程。介绍了近年来三维形状特征匹配研究领域中常用的一些测试数据库,重点探讨了非刚性三维形状的特征匹配方法,并展望了三维形状特征提取、特征匹配的未来发展方向。     

三维模型最优视角选择的粒子群优化方法

三维模型最优视角选择是指选择符合人类主观倾向最大信息量的三维物体视角.文中在预分割模型的基础上,提出一种采用粒子群优化的三维模型最优视角选择方法.首先设计了一个对候选最优视角打分的权重函数,其中的特征选取不仅考虑了视角应能够看到三维模型尽可能多的几何特征,同时也考虑了视角的舒适性;然后采用粒子群优化算法对模型进行分类别学习,获取最适合于该类模型的权重值,并获取权重函数中各个特征的权重配置.对比实验结果表明,该方法所选出的视角更加符合人类的主观倾向且不失几何信息量.     

Visual Attention for Rendered 3D Shapes

Understanding the attentional behavior of the human visual system when visualizing a rendered 3D shape is of great importance for many computer graphics applications. Eye tracking remains the only solution to explore this complex cognitive mechanism. Unfortunately, despite the large number of studies dedicated to images and videos, only a few eye tracking experiments have been conducted using 3D shapes. Thus, potential factors that may influence the human gaze in the specific setting of 3D rendering, are still to be understood. In this work, we conduct two eye‐tracking experiments involving 3D shapes, with both static and time‐varying camera positions. We propose a method for mapping eye fixations (i.e., where humans gaze) onto the 3D shapes with the aim to produce a benchmark of 3D meshes with fixation density maps, which is publicly available. First, the collected data is used to study the influence of shape, camera position, material and illumination on visual attention. We find that material and lighting have a significant influence on attention, as well as the camera path in the case of dynamic scenes. Then, we compare the performance of four representative state‐of‐the‐art mesh saliency models in predicting ground‐truth fixations using two different metrics. We show that, even combined with a center‐bias model, the performance of 3D saliency algorithms remains poor at predicting human fixations. To explain their weaknesses, we provide a qualitative analysis of the main factors that attract human attention. We finally provide a comparison of human‐eye fixations and Schelling points and show that their correlation is weak.     

一种基于局部特征的三维模型检索算法

在基于内容的三维模型检索系统中,特征提取技术是三维模型检索的关键。为此,提出基于局部特征的三维模型检索算法。定义一种新的局部特征描述符：曲度,将其作为三维模型检索时的特征。曲度作为对平均曲率与高斯曲率的校正,在不增加额外计算量的前提下,可同时克服平均曲率对平滑模型的不敏感性和高斯曲率分布较均匀的缺点,更真实地反映三维模型的局部弯曲程度。实验结果表明,以曲度作为特征进行检索,可明显提高检索的查准率,配合全局特征检索时则可在保证查全率的基础上,大幅提高检索的准确性。     

On-the-fly Curve-skeleton Computation for 3D Shapes

The curve-skeleton of a 3D object is an abstract geometrical and topological representation of its 3D shape. It maps the spatial relation of geometrically meaningful parts to a graph structure. Each arc of this graph represents a part of the object with roughly constant diameter or thickness, and approximates its centerline. This makes the curve-skeleton suitable to describe and handle articulated objects such as characters for animation. We present an algorithm to extract such a skeleton on-the-fly, both from point clouds and polygonal meshes. The algorithm is based on a deformable model evolution that captures the object's volumetric shape. The deformable model involves multiple competing fronts which evolve inside the object in a coarse-to-fine manner. We first track these fronts' centers, and then merge and filter the resulting arcs to obtain a curve-skeleton of the object. The process inherits the robustness of the reconstruction technique, being able to cope with noisy input, intricate geometry and complex topology. It creates a natural segmentation of the object and computes a center curve for each segment while maintaining a full correspondence between the skeleton and the boundary of the object.     

Fast Retrieval of Isolated Visual Shapes

Similarity-based retrieval from databases of isolated visual shapes has become an important information retrieval problem. The goal of the current work is to achieve high retrieval speed with reasonable retrieval effectiveness, and support for partial and occluded shape queries. In the proposed method, histograms of local shape parts are coded as index vectors. To increase retrieval accuracy, a rich set of parts at all scales of the shape is used; specifically, the parts are defined as connected sequences of regions in curvature scale space. To increase efficiency, structural indexing is used to compare the index vectors of the query and database shapes. In experimental evaluations, the method retrieved at least one similar shape in the top three retrieved items 99–100% of the time, depending on the database. Average retrieval times ranged from 0.7 ms on a 131-shape database to 7 ms on a 1310-shape database. The method is thus suitable for fast, approximate shape retrieval in comparison with more accurate but more costly structural matching.     

基于例子的三维运动检索

首先，运用动态聚类算法建立基于层次化运动描述的运动检索树；然后，根据得到的运动检索树，采用女近邻法则对例子运动进行分类，确定检索子集；最后，采用弹性匹配算法计算例子运动和被检索运动子集间的相似度，得到检索结果．为了提高检索效率，采用聚类算法提取运动关键帧序列表征运动，实验结果表明了文中算法的有效性。     

A Survey on 3D Visual Tracking of Multicopters

Machine Intelligence Research - Three-dimensional (3D) visual tracking of a multicopter (where the camera is fixed while the multicopter is moving) means continuously recovering the...     

三维人脸识别研究综述

近二十多年来,虽然基于图像的人脸识别已取得很大进展,并可在约束环境下获得很好的识别性能,但仍受光照、姿态、表情等变化的影响很大,其本质原因在于图像是三维物体在二维空间的简约投影.因此,利用脸部曲面的显式三维表达进行人脸识别正成为近几年学术界的研究热点.文中分析了三维人脸识别的产生动机、概念与基本过程;根据特征形式,将三维人脸识别算法分为基于空域直接匹配、基于局部特征匹配、基于整体特征匹配三大类进行综述;对二维和三维的双模态融合方法进行分类阐述;列出了部分代表性的三维人脸数据库;对部分方法进行实验比较,并分析了方法有效性的原因;总结了目前三维人脸识别技术的优势与困难,并探讨了未来的研究趋势.