基于无组织结构数据集的三维表面重建算法

三维表面重建技术具有广泛的应用前景,通用高效的重建算法是迫切需要研究的课题之一。由于三维点集分布不均匀,目前通用的基于无组织结构数据集的重建算法欠缺稳定性,应用范围受到了限制。文中提出了分布不均匀补偿的近邻点确定算法,提高了算法的稳定性和可靠性,扩展了基于无组织结构数据集表面重建算法的应用范围。实验表明通过分布不均匀补偿的离散数据集三维表面重建算法具有很好的重建效果。     

Detailed Real-Time Urban 3D Reconstruction from Video

The paper presents a system for automatic, geo-registered, real-time 3D reconstruction from video of urban scenes. The system collects video streams, as well as GPS and inertia measurements in order to place the reconstructed models in geo-registered coordinates. It is designed using current state of the art real-time modules for all processing steps. It employs commodity graphics hardware and standard CPU’s to achieve real-time performance. We present the main considerations in designing the system and the steps of the processing pipeline. Our system extends existing algorithms to meet the robustness and variability necessary to operate out of the lab. To account for the large dynamic range of outdoor videos the processing pipeline estimates global camera gain changes in the feature tracking stage and efficiently compensates for these in stereo estimation without impacting the real-time performance. The required accuracy for many applications is achieved with a two-step stereo reconstruction process exploiting the redundancy across frames. We show results on real video sequences comprising hundreds of thousands of frames.     

基于两幅图像的三维物体分层重构

文章研究在仅有两幅图像的条件下,如果摄像机内参数保持不变,如何利用场景中的结构信息实现空间物体的分层重构,研究表明,计算出无穷远平面的单应矩阵,可以仿射重构,计算出绝对二次曲线的像,就可以进一步实现欧氏重构。最后给出一个具体的实验,结果表明该算法是可行的。     

基于双幅图像三维重建的不确定性分析

由于得到基于误差传播理论的重建不确定性显式公式并没有直观性,文章在给出三维重建扰动分析模型的基础上,应用多元分析的统计方法研究了图像量化误差、匹配误差、标定误差等对重建精度的影响。采用计算机仿真图像进行实验,向重建模型中输入高斯噪声进行扰动分析,这样有利于对不确定性的评定,仿真实验证明了方法的有效性。最后,对三维重建点的伸展不确定性也进行了可视化。     

Reconstruction of 3D Object Models from Vectorised Engineering Drawings

In this paper, the problem of 3D-object model reconstruction from engineering drawing projections is analysed, and its main stages are shown. Image vectorisation and entity recognition is mentioned briefly, the main focus being editing or the parameterisation of vectorised drawings and 3D object model reconstruction from vectorised ED projections. Vectorised drawing, as a rule, do not exactly correspond to sizes and other features (touching, parallelity, perpendicularly, symmetry, collinearity, etc.) being available on the initial drawing, and this ED vector model is not suitable for direct use in CAD systems. That is why the parameterisation stage is introduced and considered in detail. An algorithm for 3D-object reconstruction from the vectorised and parameterised drawing is proposed. The algorithm is based on the detection of volumetric solid-state object components (primitives), and performing theoretic-set operations with the components. Practical experience in realising these stages is shown. Received: 23 April 1999, Received in revised form: 29 November 2000, Accepted: 07 December 2000     

Embedding visual cognition in 3D reconstruction from multi-view engineering drawings

In this paper we discuss how to reconstruct 3D models from multi-view engineering draws by employing human engineers’ approaches. Human's ‘divide and conquer’ interpretation strategy in visual cognition is simulated, and successfully carried out on the basis of spatial division of 3D object space. At first, a volume-oriented method is utilized to decompose the 3D object space in a set of 3D ‘cell-boxes’ whose three-view bounding rectangles will isolate its related sub-projections from input projections views, and in every cell-box a cell primitive is implied. Then, a 3D model of each cell primitive is ‘locally’ generated from its ‘sub-projection’ views by wire-frame oriented algorithms. The final interpretation result of the overall projection-views is a ‘Union’ of these cell primitives. To deal with the ambiguity, a visual reasoning engine is implemented on the basis of principles from Gestalt psychology. It will be activated to pick out the most reasonable interpretation, when ambiguities are generated during the reconstruction process. The section views are also incorporated in getting rid of the ambiguity. Moreover, we design a natural and convenient interaction way to encourage the user to be involved in the process while interpreting complex projections. The key steps of this human-like reconstruction approach are presented in detail.     

3-D Reconstruction of Shaded Objects from Multiple Images Under Unknown Illumination

We propose a variational algorithm to jointly estimate the shape, albedo, and light configuration of a Lambertian scene from a collection of images taken from different vantage points. Our work can be thought of as extending classical multi-view stereo to cases where point correspondence cannot be established, or extending classical shape from shading to the case of multiple views with unknown light sources. We show that a first naive formalization of this problem yields algorithms that are numerically unstable, no matter how close the initialization is to the true geometry. We then propose a computational scheme to overcome this problem, resulting in provably stable algorithms that converge to (local) minima of the cost functional. We develop a new model that explicitly enforces positivity in the light sources with the assumption that the object is Lambertian and its albedo is piecewise constant and show that the new model significantly improves the accuracy and robustness relative to existing approaches.     

岩石样本孔隙和颗粒二维图象的三维重建研究

在石油地质图象分析和模式识别中,三维物体重建是很重要的研究。该文研究了岩石样本孔隙和颗粒二维图象三维重建的一种新方法。这种方法利用从二维薄片取得的岩相学图象信息,用图象处理理论技术和数学形态学的方法生成了岩石的三维模型,对重建的三维微观结构和实际砂岩的表面细微结构进行了定量比较,比较显示,这种重建方法得到的三维模型孔隙率与原始图象基本一致,其水平面/纵切面/横切面上的颗粒长径分布与实际岩石有较好的相关性。     

Reconstruction of 3D interacting solids of revolution from 2D orthographic views

3D CAD is replacing 2D CAD to improve efficiency of product design and manufacturing. Therefore, converting legacy 2D drawings into 3D solid models is required. CSG based approaches reconstruct solid models from orthographic views more efficiently than traditional B-rep based approaches. A major limitation of CSG based approaches has been the limited domain of objects that can be handled. This paper aims at extending the capabilities of CSG based approaches by proposing a hint-based recognition of interacting solids of revolution. This approach can handle interacting solids of revolution as well as isolated solids of revolution.     

由单幅二维灰度图像重构物体表面形状*

鉴于目前很少有论文讨论完整的由单幅二维灰度图像重构物体表面形状的算法,包括它的控制参数的估计及算法的实现,介绍了一种完整的SFS算法.它在考虑自遮掩影响的情况下,有效地估计了SFS算法中涉及的各种控制参数,并引入亮度约束、灰度梯度约束和可积性约束,计算出表面高度和表面向量,实现三维重构.与传统的算法相比,本算法无论是在速度还是在精度方面都达到了比较高的水平,具有一定的应用前景.最后还指出了在MATLAB中实现需要注意的问题.     

改进流体体积法及重建光滑三维液面

通过改进流体体积法(VOF)方程求解部分，提高了离散模型中表面单元和液体内部对流的精度，从而在整体上减小了对流产生的体积误差；为逼真地展现具有复杂表面的运动液体场景，提出一种基于几何搜索的表面重建方法——种子一绕空方法．该方法可以将VOF方法生成的带缝隙表面用C^0连接的三角面片集表示，以获得光滑连续的液面表示，最后通过实例实现了较低密度网格下光滑地表现复杂液面。     

Reconstruction of 3D objects from 2D cross-sections with the 4-point subdivision scheme adapted to sets

Reconstruction of 3D objects from 2D cross-sections is an intriguing problem with many potential applications. We approach this problem through a novel multi-resolution method based on iterative refinement of the sets representing the cross-sections. To that end, we introduce a new geometric weighted average of two sets, defined for positive weights (corresponding to interpolation) and when one weight is negative (corresponding to extrapolation). This new average can be used to interpolate between cross-sections of a 3D object in a piecewise way. To obtain a smoother reconstruction of the 3D object, we adapt to sets the 4-point interpolatory subdivision scheme using the new average with both positive and negative weights. The effectiveness of the new method is demonstrated by several examples.     

Reconstruction of 3D human body pose from stereo image sequences based on top-down learning

This paper presents a novel method for reconstructing a 3D human body pose from stereo image sequences based on a top-down learning method. However, it is inefficient to build a statistical model using all training data. Therefore, the training data is hierarchically divided into several clusters to reduce the complexity of the learning problem. In the learning stage, the human body model database is hierarchically constructed by classifying the training data into several sub-clusters with silhouette images. The data of each cluster in the bottom level is represented by a linear combination of examples. In the reconstruction stage, the proposed method hierarchically searches a cluster for the best matching silhouette image using a silhouette history image (SHI). Then, the 3D human body pose is reconstructed from a depth image using a linear combination of examples method. By using depth information to reconstruct 3D human body pose, the similar poses in silhouette images are estimated as different 3D human body poses. The experimental results demonstrate that the proposed method is efficient and effective for reconstructing 3D human body poses.