立体目标的宽基线图像匹配

为了匹配立体目标的图像特征,提出一种仿射不变的局部特征提取算法。根据高斯滤波器的形状和大小要与图像结构相适应的原理,该算法利用图像中的最大稳定极值区域(MSER)的协方差矩阵衡量局部图像结构,并将局部图像结构变换到圆形高斯滤波器适用的形式下,以解决视角和尺度变化问题。为了保证图像变换的正确性,采用旋转压缩的方式将各向异性的图像结构变换为各向同性的图像结构。最后在各向同性的图像结构上提取尺度不变特征变换(SIFT)特征点,并将SIFT特征点的坐标变回原图像坐标。实验结果表明该算法提取的局部特征是完全仿射不变的,在立体目标的宽基线图像匹配中表现出良好的效果。     

3D Image Synthesis for B-Reps Objects

This paper presents a new algorithm for generating 3D images of B-reps objects with trimmed surface boundaries.The 3D image is a discrete voxel-map representation within a Cubic Frame Buffer (CFB).The definition of 3D images for curve,surface and solid object are introduced which imply the connectivity and fidelity requirements.Adaptive Forward Differencing matrix (AFD-matrix) for 1D-3D manifolds in 3D space is developed.By setting rules to update the AFD-matrix,the forward difference direction and stepwise can be adjusted.Finally,an efficient algorithm is presented based on the AFD-matrix concept for converting the object in 3D space to 3D image in 3D discrete space.     

A conceptual schema-based temporal meta database schemas generation technique for 3D objects

In this paper, a temporal meta database for three-dimensional (3D) objects whose properties and relationships are supported by valid time is introduced. Based on our proposed temporal object-oriented conceptual schema model, a conceptual schema of the temporal meta database can be generated from a 3D graphical data source and other particular application requirements. Based on our proposed temporal object relational data model with attribute timestamping, logical schemas of the temporal meta database can be systematically and automatically generated from the conceptual schema. From the temporal meta database, non-temporal/temporal metadata about temporal 3D objects are available for temporal information system users. Convenient access using database languages such as SQL can be performed. Queries over 3D objects using a temporal object relational SQL are demonstrated.     

Watermarking 3D objects for verification

We introduce and investigate the fundamental similarities and differences of watermarking 3D graphic models compared to 2D images, and propose some solutions to address a class of applications of digital watermarking-the verification of 3D polygonal models. To our knowledge, watermarking of 3D objects for verification purposes has not been addressed in any published literature. The proposed scheme, in its present form, is not intended for use in applications that require robust watermarks. One recent work in 3D data hiding addressed applications requiring robust means of hiding data. We first introduce digital watermarking, discuss its goals and application domains, and explain the different categories of watermarks. We believe the goals and applications will remain fairly similar for 2D images and 3D models     

3D image acquisition and NURBS based geometry modelling of natural objects

This paper presents a recently developed Image Acquisition–Geometric Modelling system for the construction of geometric models of natural or artificial objects. This construction is achieved in a two-step procedure. First, the object of interest is digitised, i.e. points on the surface of the object are computed. Then, based on the cloud of digitised 3D points, an approximating surface, a geometric model of the object of interest, is constructed. Coupled with a mesh generation package, the system presented allows for further processing and analysis of the resulting model instead of the real object itself.     

三维图像虚拟视点生成优化研究仿真

为完整获取立体场景中所有视点信息,提出基于几何模型的立体图像虚拟视点生成方法.结合空间距离与像素差值两个影响因素,建立双边滤波器的滤波函数,定义权重系数,调节邻近度因子与亮度相似性因子的衰减性,得到滤波后的像素值;采集不同视角下二维图像,确定三维空间与二维图像间的几何映射关系,经过计算横向与纵向曲率、物体横向分割等过程...     

再现3D对象

多亏有了Google上的一种免费工具,3D建模变得不再是一个痛苦而笨拙的过程。Jerome Turner介绍SketchUp的主要功能。     

R-VPCG: RGB image feature fusion-based virtual point cloud generation for 3D car detection

Although 3D object detection methods based on feature fusion have made great progress, the methods still have the problem of low precision due to sparse point clouds. In this paper, we propose a new feature fusion-based method, which can generate virtual point cloud and improve the precision of car detection. Considering that RGB images have rich semantic information, this method firstly segments the cars from the image, and then projected the raw point clouds onto the segmented car image to segment point clouds of the cars. Furthermore, the segmented point clouds are input to the virtual point cloud generation module. The module regresses the direction of car, then combines the foreground points to generate virtual point clouds and superimposed with the raw point cloud. Eventually, the processed point cloud is converted to voxel representation, which is then fed into 3D sparse convolutional network to extract features, and finally a region proposal network is used to detect cars in a bird’s-eye view. Experimental results on KITTI dataset show that our method is effective, and the precision have significant advantages compared to other similar feature fusion-based methods.     

Direct shape optimization for strengthening 3D printable objects

Recently there has been an increasing demand for software that can help designers create functional 3D objects with required physical strength. We introduce a generic and extensible method that directly optimizes a shape subject to physical and geometric constraints. Given an input shape, our method optimizes directly its input mesh representation until it can withstand specified external forces, while remaining similar to the original shape. Our method performs physics simulation and shape optimization together in a unified framework, where the physics simulator is an integral part of the optimizer. We employ geometric constraints to preserve surface details and shape symmetry, and adapt a second‐order method with analytic gradients to improve convergence and computation time. Our method provides several advantages over previous work, including the ability to handle general shape deformations, preservation of surface details, and incorporation of user‐defined constraints. We demonstrate the effectiveness of our method on a variety of prinTable 3D objects through detailed simulations as well as physical validations.     

Comparative analysis of shape descriptors for 3D objects

Multimedia Tools and Applications - One of the basic characteristics of an object is its shape. Several research areas in mathematics and computer science have taken an interest in object...     

Algorithms for construction digital 3D models for unique objects

Problems of development and analysis of construction high-detailed digital models of an object surface are addressed. It is also supposed that simulated objects are not standard; i.e., they are bounded by a surface of a complex form, and their digital representation require generating a very large number of points. Special attention is paid to problems of constructing a hierarchical structure of algorithms, including the analysis of various strategies of condensing points and surface approximation. For a number of examples, the capabilities of the developed technique are demonstrated for various objects and different types of imagery.     

Computing hierarchical curve-skeletons of 3D objects

A curve-skeleton of a 3D object is a stick-like figure or centerline representation of that object. It is used for diverse applications, including virtual colonoscopy and animation. In this paper, we introduce the concept of hierarchical curve-skeletons and describe a general and robust methodology that computes a family of increasingly detailed curve-skeletons. The algorithm is based upon computing a repulsive force field over a discretization of the 3D object and using topological characteristics of the resulting vector field, such as critical points and critical curves, to extract the curve-skeleton. We demonstrate this method on many different types of 3D objects (volumetric, polygonal and scattered point sets) and discuss various extensions of this approach.     

Registration of 3D objects and surfaces

An approach to the problem of comparative analysis of objects and their surfaces that arises in medical imaging is presented and illustrated with an application to postsurgical bone-graft separation. A common requirement in medical imaging applications is the registration of multiple representations of the object prior to mensuration. The modeling of the registration process and the registration system are described. The measurement of change in volume of bone grafts implanted inside the human body in a corrective surgical procedure is discussed, and the results are evaluated     

Hole filling in 3D volumetric objects

The construction of hole filling (or hole segmentation) method for 3D volumetric images is a new challenging issue in computer science. It needs a geometrical approach since from a topological point of view 3D holes (tunnels) are not well-delimited subsets of three dimensional space. In this paper, the authors propose an original, efficient, flexible algorithm of hole filling for volumetric objects. The algorithm has been tested on artificial objects and very complicated crack propagation tomography images. The qualitative results, quantitative results and features of proposed approach are presented in the paper. According to our knowledge it is the first algorithm of hole filling for volumetric objects.     

Optimal strategies for creating paper models from 3D objects

Paper is an underrated medium in multimedia technology. Rather than showing printed information only, it can also be used for creating real paper models from virtual objects by means of glue and scissors. This requires to compute a planar cut-out sheet from a 3D model. However, faces forming a model in 3D will often overlap once unfolded. While 3D space leaves much possibility for a non-intersecting topology of faces, they tend to intersect easily in the planar projection of the cut-out sheet. But overlaps are not the only problem. In some cases, neighboring faces enclose such a small angle that they are difficult to cut out and glue together. Unfolding a virtual model involves to decide which edges of a 3D model to cut first. A carefully chosen order can help to avoid the above mentioned problems in many cases. Finding the optimal order, however, is an NP-complete problem. In this paper, we develop and analyze a number of strategies that generate sheets which can be crafted easily and which yield high quality results.     

3D modeling of optically challenging objects

We present a system for constructing 3D models of real-world objects with optically challenging surfaces. The system utilizes a new range imaging concept called multi-peak range imaging, which stores multiple candidates of range measurements for each point on the object surface. The multiple measurements include the erroneous range data caused by various surface properties that are not ideal for structured-light range sensing. False measurements generated by spurious reflections are eliminated by applying a series of constraint tests. The constraint tests based on local surface and local sensor visibility are applied first to individual range images. The constraint tests based on global consistency of coordinates and visibility are then applied to all range images acquired from different viewpoints. We show the effectiveness of our method by constructing 3D models of five different optically challenging objects. To evaluate the performance of the constraint tests and to examine the effects of the parameters used in the constraint tests, we acquired the ground truth data by painting those objects to suppress the surface-related properties that cause difficulties in range sensing. Experimental results indicate that our method significantly improves upon the traditional methods for constructing reliable 3D models of optically challenging objects.