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.     

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.     

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。     

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。     

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.     

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.     

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.     

3D动画技术在移动平台上的研究与实现

本文介绍了移动3D技术的发展,简要介绍了关键帧动画、变形动画、骨骼蒙皮动画三种动画的原理,详细分析了M3G平台上的动画实现原理和实现方法,并给出了M3G平台动画实现的一个例子。     

基于内容的图像检索技术研究

随着数字图像在多媒体领域的广泛应用,对基于内容的图像检索技术的需求也不断增加.基于内容的图像检索技术总体上可以分为两部分:图像特征提取、图像特征的索引与匹配.图像特征提取主要解决如何在数学上有效地描述一幅图像.文中分别介绍了颜色、形状和纹理特征提取算法近年来的研究成果.图像特征索引与匹配,主要解决如何根据特征描述判断图像间的相似程度,并准确、快速列出图像库中与检索图像相似的图像,分别介绍了相似度测量方法、聚类与分类技术、相关反馈技术三类技术的主要研究成果.最后对基于内容的图像检索技术的研究难点进行了讨论,对未来可能的研究方向进行了展望.     

3D动画技术在移动平台上的研究与实现

本文介绍了移动3D技术的发展，简要介绍了关键帧动画、变形动画、骨骼蒙皮动画三种动画的原理，详细分析了M3G平台上的动画实现原理和实现方法，并给出了M3G平台动画实现的一个例子。     

基于内容的视频检索技术

该文系统地介绍了实现基于内容的视频检索的一般过程,从分析视频检索的系统结构出发,全面地探讨了系统所涉及的视频结构的构造、视频检索的工作原理、关键帧提取技术、从视频流中构造场景或组的技术、特征提取技术以及视频检索、浏览和检索反馈技术,重点分析了一些关键技术中的算法以及未来的研究重点。