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.     

基于三维加权和双域滤波的螺旋CT伪影校正

螺旋CT重建会受到锥束伪影和风车伪影的影响,锥束伪影是由于锥角和螺距过大而导致的,而风车伪影由纵向方向采样不足引起,为了降低锥束伪影与风车伪影对CT图像的影响,提出一种螺旋CT伪影校正算法;首先采用三维加权螺旋FDK算法进行重建,有效去除重建图像中的锥束伪影,然后采用改进的双域滤波算法对含风车伪影图像进行校正;三维加权螺旋FDK算法通过对大锥角的射线给予不利权重来抑制锥束伪影,改进的双域滤波算法可以在去除风车伪影的同时保留更多的细节;计算机仿真实验结果表明,该算法能有效地抑制重建图像中的锥束伪影和风车伪影,提高CT图像的质量。     

物体多视角三维图象对齐复位的一种新方法

为了高质量准确地对物体多视角三维图象进行快速对齐复位，提出了一种将多个视角三维自然曲面数据精确对齐复位于同一坐标系中的新型迭代方法，该方法根据三维自然曲面的共同特性，并采用不同视角中对应曲面部分的若干单元面法向量误差最小及其对应顶点距离最小的迭代准则来进行对齐复位，同时还详细地叙述了迭代算法的过程，并讨论了提高算法速度与降低累积误差的方法，实例表明，该算法在无需约束三维数据采集过程和不额外增加三维数据采集设备及操作的情况下，不仅速度快，而且由复位后的各视角三维曲面形成的整体表面效果自然逼真。     

Research on the effect of contrast enhancement and illumination condition on 3D visual fatigue

3D visual comfort can be influenced by such common factors as binocular parallax, 3D image contrast, viewing distance, and illumination condition. This paper investigates the effect of contrast enhancement and illumination condition on 3D visual fatigue by performing a visual fatigue measurement experiment, of which subjects need to watch 3D images under two illumination conditions and finish a comfort judgment task. The proportion of discomfort images, the subjective evaluation of visual fatigue under 100 lux and 500 lux illumination conditions, the effect of image contrast enhancement on 3D visual fatigue, and the relationship between visual fatigue and proportion of discomfort images were analyzed, respectively. The experimental results showed that both the contrast enhanced by Laplacian algorithm and low illumination condition have positive influence on 3D visual perception of eyes; the 3D visual fatigue of contrast enhanced by Laplacian algorithm under low illumination condition was less than other situations in the experiment. Moreover, it was examined that the proportion of discomfort images can be potential prediction indicator of the 3D visual fatigue.     

一个基于深度图像的三维模型检索算法

三维模型检索是现在的研究热点,提出一种基于深度图像的三维模型检索算法。对三维模型进行规范化处理,采用基于正交投影的方法计算三维模型在其包围立方体的六个面上的深度图像;提取深度图像的边界方向直方图和Zernike矩特征;利用特征距离度量进行三维模型检索,并采用相关反馈技术实现权值的调整,得到用户最满意的目标检索模型。对比实验表明,该算法避免了传统视觉图像丢失三维模型空间信息的缺点,有效地提高了检索的精确性和鲁棒性。     

Illumination normalization of facial images by reversing the process of image formation

Variations in illumination degrade the performance of appearance based face recognition. We present a novel algorithm for the normalization of color facial images using a single image and its co-registered 3D pointcloud (3D image). The algorithm borrows the physically based Phong’s lighting model from computer graphics which is used for rendering computer images and employs it in a reverse mode for the calculation of face albedo from real facial images. Our algorithm estimates the number of the dominant light sources and their directions from the specularities in the facial image and the corresponding 3D points. The intensities of the light sources and the parameters of the Phong’s model are estimated by fitting the Phong’s model onto the facial skin data. Unlike existing approaches, our algorithm takes into account both Lambertian and specular reflections as well as attached and cast shadows. Moreover, our algorithm is invariant to facial pose and expression and can effectively handle the case of multiple extended light sources. The algorithm was tested on the challenging FRGC v2.0 data and satisfactory results were achieved. The mean fitting error was 6.3% of the maximum color value. Performing face recognition using the normalized images increased both identification and verification rates.     

Spatial Modelling for Mobile Robot’s Vision-based Navigation

We present an algorithm to model 3D workspace and to understand test scene for mobile robot’s navigation or human computer interaction. This has done by line-based modeling and recognition algorithm. Line-based recognition using 3D lines has been tried by many researchers however its reliability still needs improvement due to ambiguity of 3D line feature information from original images. To improve the outcome, we approach firstly to find real planes using given 3D lines and then to implement recognition process. The methods we use are principle component analysis (PCA), plane sweep, occlusion query, and iterative closest point (ICP). During the implementation, we also use 3D map information for localization. We apply this algorithm to real test scene images and find out our result can be useful to identify doors or walls in indoor environment with better efficiency.     

多参数加权的无缝纹理映射算法

目的 针对基于图像3维重建中纹理映射存在缝隙的问题,提出一种多参数加权的无缝纹理映射算法。方法 算法根据图像的标定信息对三角格网进行聚类分割,将重建模型聚类成不同参考图像的网格贴片,并对贴片排序生成纹理图像,加权融合重建顶点的法线角度、图像视点、模型深度等信息生成纹理贴片像素,最后采用多分辨率分解融合技术消除纹理贴片缝隙,实现无缝的纹理映射。结果 对不同的测试数据进行了验证,本文算法在保持一定清晰度的前提下消除了纹理的缝隙,即使对于构网误差较大的区域也能得到较为满意的结果,同时本文算法支持大数据的3维纹理映射。结论 提出了一种无缝的纹理映射算法,算法通过构造一个平滑的加权方程融合多源信息消除纹理的接缝,实验结果表明了本文算法的有效性及实用性,得到了高保真的无缝纹理映射效果,可应用到城市级别的大场景3维重建领域。     

基于未标定多幅图的三维重建算法

为得到鲁棒的三维重建效果,提出了一种基于未标定多幅图像的三维重建算法。该算法首先采用Harris算法检测特征点,针对双向匹配算法匹配速度慢的缺点,使用改进的双向匹配算法进行特征点匹配,在已知摄像机参数的情况下进行两幅图的三维重建;接着采用四元数算法进行坐标转换,将由每两幅图得到的不同部分的重建结果转移到同一坐标系下,实现了多幅图像的三维重建;最后利用集束调整优化重建结果。实验结果证明,该算法能获得比较满意的重建效果。     

局部均值噪声估计的盲3维滤波降噪算法

目的 图像在获取和传输的过程中很容易受到噪声的干扰,图像降噪作为众多图像处理系统的预处理模块在过去数十年中得到了广泛的研究。在已提出的降噪算法中,往往采用加性高斯白噪声模型AWGN（additive white Gaussian noise）为噪声建模,噪声水平（严重程度）由方差参数控制。经典的BM3D 3维滤波算法属于非盲降噪（non-blind denoising algorithm）算法,在实际使用中需要由人工评估图像噪声水平并设置参数,存在着噪声评估值随机性大而导致无法获得最佳降噪效果的问题。为此,提出了一种新的局部均值噪声估计（LME）算法并作为BM3D算法的前置预处理模块。方法 本文专注于利用基于自然统计规律（NSS）的图像质量感知特征和局部均值估计技术构建图像噪声水平预测器,并通过它高效地获得噪声图像中准确的噪声水平值。关于自然场景统计方面的研究表明,无失真的自然场景图像在空域或者频率域上具有显著的统计规律,一旦受到噪声干扰会产生规律性的偏移,可以提取这些特征值作为反映图像质量好坏的图像质量感知特征。另外,局部均值估计因其简单而高效率的预测特性被采用。具体实现上,在具有广泛代表性且未受噪声干扰图像集合上添加不同噪声水平的高斯噪声构建失真图像集合,然后利用小波变换对这些失真图像进行不同尺度和不同方向的分解,再用广义高斯分布模型（GGD）提取子带滤波系数的统计信息构成描述图像失真程度的特征矢量,最后用每幅失真图像上所提取的特征矢量及对其所施加的高斯噪声水平值构成了失真特征矢量库。在降噪阶段,用相同的特征提取方法提取待降噪的图像的特征矢量并在失真特征矢量库中检索出与之类似的若干特征矢量及它们所对应的噪声水平值,然后用局部均值法估计出待降噪图像中高斯噪声大小作为经典BM3D算法的输入参数。结果 改进后的BM3D算法转换为盲降噪算法,称为BM3D-LME（block-matching and 3D filtering based on local means estimation）算法。准确的噪声估计对于诸如图像降噪,图像超分辨率和图像分割等图像处理任务非常重要。已经验证了所提出噪声水平估计算法的准确性、鲁棒性和有效性。结论 相对人工进行噪声估计,LME算法能够准确、快速地估算出任意待降噪图像中的噪声大小。配合BM3D算法使用后,有效提高了它的实际降噪效果并扩大它的应用范围。     

Automatic facial feature extraction and 3D face modeling using two orthogonal views with application to 3D face recognition

We present a fully automated algorithm for facial feature extraction and 3D face modeling from a pair of orthogonal frontal and profile view images of a person's face taken by calibrated cameras. The algorithm starts by automatically extracting corresponding 2D landmark facial features from both view images, then compute their 3D coordinates. Further, we estimate the coordinates of the features that are hidden in the profile view based on the visible features extracted in the two orthogonal face images. The 3D coordinates of the selected feature points obtained from the images are used first to align, then to locally deform the corresponding facial vertices of the generic 3D model. Preliminary experiments to assess the applicability of the resulted models for face recognition show encouraging results.     

Topological Repairing of 3D Digital Images

We present here a new randomized algorithm for repairing the topology of objects represented by 3D binary digital images. By “repairing the topology”, we mean a systematic way of modifying a given binary image in order to produce a similar binary image which is guaranteed to be well-composed. A 3D binary digital image is said to be well-composed if, and only if, the square faces shared by background and foreground voxels form a 2D manifold. Well-composed images enjoy some special properties which can make such images very desirable in practical applications. For instance, well-known algorithms for extracting surfaces from and thinning binary images can be simplified and optimized for speed if the input image is assumed to be well-composed. Furthermore, some algorithms for computing surface curvature and extracting adaptive triangulated surfaces, directly from the binary data, can only be applied to well-composed images. Finally, we introduce an extension of the aforementioned algorithm to repairing 3D digital multivalued images. Such an algorithm finds application in repairing segmented images resulting from multi-object segmentations of other 3D digital multivalued images.

从阴影恢复形状的径向基函数反射模型研究

目的 为解决传统阴影恢复形状（SFS）算法由于光源方向初始信息估计不准确,恢复的物体表面过于光滑,3维表面形状误差较大等问题,建立了基于径向基函数神经网络的反射模型,并对传统的神经网络进行了改进。方法 建立的基于径向基函数（SFS）神经网络的从阴影恢复形状反射模型代替了传统方法中采用的理想朗伯体表面反射模型。该模型利用径向基函数优秀的局部映射和函数逼近能力来处理SFS问题,通过网络训练过程中的权值代替物体所受到的初始光源信息,解决了传统算法在进行计算时,必须已知光源参数的限制。在该网络模型中添加自适应学习率算法,加速网络的收敛和训练速度。结果 针对SFS问题处理的两幅经典合成图像以及两幅实际图像进行了实验,实验结果表明,改进后的算法在3维视觉效果和3维形状信息的恢复方面都明显优于传统算法。归一化后的3维高度误差结果相比传统算法缩小了60%以上,而且同时适用合成图像和实际图像;自适应学习率的加入,使得网络的训练速度大大加快,对一幅128×128像素的图像,运算速度提升了50%。结论 本文针对SFS问题建立了基于RBF神经网络的从阴影恢复形状反射模型,利用网络模型中的参数代替SFS问题中的初始光源信息,通过最优化方法求解SFS问题。并针对传统的神经网络固定学习率造成网络收敛速度慢,容易陷入局部极小值的问题,加入了自适应学习率算法。实验结果表明,改进后的算法在处理该SFS问题时表现了优秀的性能,适用范围更广,收敛速度更快。     

Detection of the non-topology preservation of Ma and Sonka’s algorithm,by the use of P-simple points

In 1996, Ma and Sonka proposed a thinning algorithm which yields curve skeletons for 3D binary images [C. Ma, M. Sonka, A fully parallel 3D thinning algorithm and its applications, Comput. Vis. Image Underst. 64 (3) (1996) 420–433]. This algorithm is one of the most referred thinning algorithms in the context of digital topology: either by its use in medical applications or for comparisons with other thinning algorithms.In 2007, Wang and Basu [T. Wang, A. Basu, A note on ‘a fully parallel 3D thinning algorithm and its applications’, Pattern Recognit. Lett. 28 (4) (2007) 501–506] wrote a paper in which they claim that Ma and Sonka’s 3D thinning algorithm does not preserve topology. As they highlight in their paper, a counter-example was given in 2001, in Lohou’s thesis [C. Lohou, Contribution à l’analyse topologique des images: étude d’algorithmes de squelettisation pour images 2D et 3D selon une approche topologie digitale ou topologie discrète. Ph.D. thesis, University of Marne-la-Vallée, France, 2001].In this paper, it is shown how P-simple points have guided the author towards a proof that Ma and Sonka’s algorithm does not always preserve topology. Moreover, the reasoning being very general, it could be reused for such a purpose, i.e., to simplify the proof on the non-topology preservation.     

三维曲面的特征描述和特征匹配

本文提出了一种新的三维曲面特征描述算法,将二维图像上的特征描述思想推广到三维网格。算法将三维网格表示成从顶点到高斯曲率的映射函数,从而获得可类比于二维图像的相似性。借助于法线和梯度建立局部球坐标系,通过二维统计直方图对特征点邻域的几何信息进行描述,使得特征描述具有平移、旋转和缩放不变性,最终生成128维的特征向量(特征描述符)。基于特征向量,我们实现了多分辨率和异拓扑网格下的特征匹配,展示并分析了实验结果。本文的研究动机来源于三维扫描建模以及多视点三维重建技术中对特征描述和特征匹配的需求,主要的应用方向包括:扫描配准、模型注册、动画跟踪、对称检测和模型检索。     

Diffeomorphic 3D Image Registration via Geodesic Shooting Using an Efficient Adjoint Calculation

In the context of large deformations by diffeomorphisms, we propose a new diffeomorphic registration algorithm for 3D images that performs the optimization directly on the set of geodesic flows. The key contribution of this work is to provide an accurate estimation of the so-called initial momentum, which is a scalar function encoding the optimal deformation between two images through the Hamiltonian equations of geodesics. Since the initial momentum has proven to be a key tool for statistics on shape spaces, our algorithm enables more reliable statistical comparisons for 3D images.     

一种由未定标图象估计三维射影不变量的新算法

本文提出了一种由未定标图象估计三维射不变量的新算法。实验结果表明了本算法的有效性。     

Projective reconstruction of ellipses from multiple images

This paper presents a new approach for reconstructing 3D ellipses (including circles) from a sequence of 2D images taken by uncalibrated cameras. Our strategy is to estimate an ellipse in 3D space by reconstructing N(≥5) 3D points (called representative points) on it, where the representative points are reconstructed by minimizing the distances from their projections to the measured 2D ellipses on different images (i.e., 2D reprojection error). This minimization problem is transformed into a sequence of minimization sub-problems that can be readily solved by an algorithm which is guaranteed to converge to a (local) minimum of the 2D reprojection error. Our method can reconstruct multiple 3D ellipses simultaneously from multiple images and it readily handles images with missing and/or partially occluded ellipses. The proposed method is evaluated using both synthetic and real data.     

基于GPU的3D距离变换*

距离变换在图像处理中有着非常广泛的应用。由于3D图像数据的复杂性,传统基于CPU的3D距离变换效率较低。为此,研究了将3D图像数据有效地组织到纹理中存储的方法,设计并实现了基于GPU的3D距离变换并行算法。实验结果表明,相对基于CPU的算法,该方法具有非常高的加速比。