基于投影图像 SURF 特征提取的三维模型配准

针对传统三维模型配准方法存在对点云初始位置有一定要求、模型配准的精度有 时不高等问题,提出了一种基于三维模型投影图像 SURF 特征提取的三维模型配准方法。首先 通过扫描三维模型数据确定投影图像的范围,判断每个投影图像像素所隶属的模型网格,并求 解从投影图像到纹理图像的映射关系,从而获取二维投影图像;然后对这两幅投影图像分别进 行 SURF 特征点的选取与特征值的计算,并按 SURF 特征值进行特征匹配,再根据投影图像像 素点与三维网格端点的映射关系计算三维特征点对;最后通过匹配的特征点对求取模型变换矩 阵完成三维模型的配准。实验结果表明,该方法在配准时间变化不大的前提下,有效提高了配 准精度,并具有较好的鲁棒性。     

一种基于平面模板的虚实配准算法

虚实配准是增强现实的关键技术。因为有运算量小实时性强的特点，利用平面模板进行虚实配准被广泛使用。本文算法利用平面模板进行虚实配准中的单应性映射关系，建立从平面模板坐标系到摄像机坐标系3维空间坐标转换和从摄像机坐标系到投影平面的3维-2维空间坐标转换，既减小了运算量，又解决了人工定标的问题。在实现虚实配准的基础上，进一步探讨了配准的优化问题，对关键的单应性矩阵进行优化筛选，提高虚实配准的强劲性，实现部分标志点被遮挡情况下的虚实配准。实验结果证明，本文算法成功实现了虚实配准，并在抗遮挡性上有强劲的表现。     

PTZ摄像机视频与三维模型的配准技术研究

针对基于投影纹理映射的虚实融合系统,提出了一种PTZ摄像机视频与三维模型实时配准的技术.选取PTZ摄像机若干特定姿态的子图像组成一张全景图像,进行最优匹配图像的搜索,用SURF图像配准的方法对实时视频图像进行透视变换,利用最优匹配图像的三维投影信息将实时视频图像精确投影到三维模型中.实验结果表明,该算法具有较高的准确性,适用于虚实融合系统中PTZ摄像机视频的三维配准.     

一种二维工程图向三维模型的尺寸映射算法

针对当前制造型企业内部存在二维工程图和三维CAD模型之间的数据共享问题,提出一种基于图匹配的二维工程图向三维CAD模型的尺寸映射算法,将二维工程图中的尺寸信息直接映射到对应的三维CAD模型上。首先将三维模型进行投影得到投影视图,然后将投影视图和二维工程图转化为一种空间关系图,对两个空间关系图进行图匹配,找出图元间的映射关系,并且利用工程图中尺寸标注的特点对算法进行改进,提高算法效率和可靠性。实验结果表明,该算法可以很好的实现二维工程图向三维CAD模型的尺寸映射。     

基于图像的点云初始配准

针对地面激光点云的分辨率不同等问题,提出一种不借助额外装置,把二维图像与三维点云相结合的初始配准方法。把不同分辨率点云均匀滤波,根据深度值把三维点云转化为二维灰度图,利用SURF算法提取图像的特征匹配点对;根据映射关系找到三维特征匹配点,利用单位四元数法求出变换矩阵完成点云初始配准。实验结果表明,该算法对于地面激光数据的配准,无论从配准的精度上还是时间上均有很大提高。     

基于GPU的实时三维点云数据配准研究

在三维重建中,不同摄像机坐标系下点云配准耗时过多。为此,提出一种基于图形处理单元(GPU)的实时三维点云数据配准算法。利用投影映射法获取匹配点对,使用点到切平面距离最小化方法计算变换矩阵,通过GPU多线程并行处理大规模图像数据。实验结果表明,对于分别包含307 200个数据的2帧点云,在保持原有配准效果的基础上,该算法的最优耗时仅为基于CPU的最近邻迭代算法的11.9%。     

基于机器学习和几何变换的实时2D/3D脊椎配准

在图像引导的脊柱手术中,实时高效的2D/3D配准是一项重要且具有挑战性的任务.通常的2D/3D配准一般是将三维图像投影到二维平面,然后进行2D/2D的配准.由于投影空间涉及到3个平移以及3个旋转参数,其投影空间的复杂度为O（n6）,使得配准很难兼具高准确性和高实时性.本文提出了一个结合机器学习与几何变换的2D/3D配准方法,首先,使用统计形状模型对目标脊椎进行建模,并构建了一种新的投影方式,使得6个投影参数中的4个可以使用几何的方法计算出来;接下来利用回归学习的方法学习目标脊椎的形状与投影参数之间的关系;最终,结合学到的关系和几何变换完成配准.本方法的两个姿态参数的平均预测误差为0.84°和0.81°,平均目标配准误差（Mean target registration error,mTRE）为0.87mm,平均配准时间为0.9s.实验结果表明本方法具有很好的实时性和准确性.     

面向大规模场景的三维线段检测算法

为了实现大规模重建场景的三维轮廓高效提取,提出了一种基于重投影的三维线段检测算法.在基于二维线段检测器的线段检测与基于运动恢复结构的重建基础上,根据摄像机矩阵对空间点云进行重投影;通过弱匹配关系寻找最佳重投影线段,并利用重投影索引推断出三维线段;最后通过对空间短线段进行延伸获得三维轮廓线,并采用空间点云的平面聚类消除重...     

基于投影近似不变性的3D-2D医学图像配准

研究了同一病人的MRA和DSA图像之间的3D-2D配准问题，提出了一种基于投影近似不变性的配准算法，即在同一视角下，同一病人的三维MRA血管骨架的投影与二维DSA的骨架保持一致。通过定义二者之间的代价函数，并利用牛顿迭代法可得到视角参数的最优解。针对临床采集的MRA和DSA数据进行了实验，取得了较为满意的结果。     

基于二维超声- 三维 CT 配准的肾脏穿刺定位方法可行性研究

医学影像引导的经皮肾穿刺手术是经皮肾镜取石术中建立手术通道的重要手段,高质量的 实时医学图像可以提高术中穿刺精度,减少手术风险。针对自由呼吸下经皮肾穿刺靶点的导航定位问 题,该研究提出了一种基于术中二维超声-术前三维 CT 实时配准的肾脏穿刺定位方法。首先对肾脏轮 廓特征的二维超声图像和三维 CT 图像进行由粗到精的快速配准,然后通过超声探头标定,将配准融合 后的图像注册到手术空间,实现穿刺靶点的实时定位。人体腹部模型实验结果表明,超声探头标定均 方根误差为 0.998 mm,二维超声和三维 CT 数据配准误差为 0.709 mm,平均配准运算时间为 1.15 s,最 终的平均定位误差为 2.265 mm。     

High‐resolution autostereoscopic 3‐D projection display with a space‐dividing iris‐plane shutter

Abstract— A high‐resolution autostereoscopic 3‐D projection display with a polarization‐control space dividing the iris‐plane liquid‐crystal shutter is proposed. The polarization‐control iris‐plane shutter can control the direction of stereo images without reducing the image quality of the microdis‐play. This autostereoscopic 3‐D projection display is 2‐D/3‐D switchable and has a high resolution and high luminance. In addition, it has no cross‐talk between the left and right viewing zones, a simple structure, and the capability to show multi‐view images.     

2D/3D image registration using regression learning

In computer vision and image analysis, image registration between 2D projections and a 3D image that achieves high accuracy and near real-time computation is challenging. In this paper, we propose a novel method that can rapidly detect an object’s 3D rigid motion or deformation from a 2D projection image or a small set thereof. The method is called CLARET (Correction via Limited-Angle Residues in External Beam Therapy) and consists of two stages: registration preceded by shape space and regression learning. In the registration stage, linear operators are used to iteratively estimate the motion/deformation parameters based on the current intensity residue between the target projection(s) and the digitally reconstructed radiograph(s) (DRRs) of the estimated 3D image. The method determines the linear operators via a two-step learning process. First, it builds a low-order parametric model of the image region’s motion/deformation shape space from its prior 3D images. Second, using learning-time samples produced from the 3D images, it formulates the relationships between the model parameters and the co-varying 2D projection intensity residues by multi-scale linear regressions. The calculated multi-scale regression matrices yield the coarse-to-fine linear operators used in estimating the model parameters from the 2D projection intensity residues in the registration. The method’s application to Image-guided Radiation Therapy (IGRT) requires only a few seconds and yields good results in localizing a tumor under rigid motion in the head and neck and under respiratory deformation in the lung, using one treatment-time imaging 2D projection or a small set thereof.     

Model-based recognition of 3D objects from single images

In this work, we treat major problems of object recognition which have received relatively little attention lately. Among them are the loss of depth information in the projection from a 3D object to a single 2D image, and the complexity of finding feature correspondences between images. We use geometric invariants to reduce the complexity of these problems. There are no geometric invariants of a projection from 3D to 2D. However, given certain modeling assumptions about the 3D object, such invariants can be found. The modeling assumptions can be either a particular model or a generic assumption about a class of models. Here, we use such assumptions for single-view recognition. We find algebraic relations between the invariants of a 3D model and those of its 2D image under general projective projection. These relations can be described geometrically as invariant models in a 3D invariant space, illuminated by invariant “light rays,” and projected onto an invariant version of the given image. We apply the method to real images     

Calibration of Central Catadioptric Cameras Using a DLT-Like Approach

In this study, we present a calibration technique that is valid for all single-viewpoint catadioptric cameras. We are able to represent the projection of 3D points on a catadioptric image linearly with a 6×10 projection matrix, which uses lifted coordinates for image and 3D points. This projection matrix can be computed from 3D–2D correspondences (minimum 20 points distributed in three different planes). We show how to decompose it to obtain intrinsic and extrinsic parameters. Moreover, we use this parameter estimation followed by a non-linear optimization to calibrate various types of cameras. Our results are based on the sphere camera model which considers that every central catadioptric system can be modeled using two projections, one from 3D points to a unitary sphere and then a perspective projection from the sphere to the image plane. We test our method both with simulations and real images, and we analyze the results performing a 3D reconstruction from two omnidirectional images.     

Weakly Supervised Part-wise 3D Shape Reconstruction from Single-View RGB Images

In order for the deep learning models to truly understand the 2D images for 3D geometry recovery, we argue that single-view reconstruction should be learned in a part-aware and weakly supervised manner. Such models lead to more profound interpretation of 2D images in which part-based parsing and assembling are involved. To this end, we learn a deep neural network which takes a single-view RGB image as input, and outputs a 3D shape in parts represented by 3D point clouds with an array of 3D part generators. In particular, we devise two levels of generative adversarial network (GAN) to generate shapes with both correct part shape and reasonable overall structure. To enable a self-taught network training, we devise a differentiable projection module along with a self-projection loss measuring the error between the shape projection and the input image. The training data in our method is unpaired between the 2D images and the 3D shapes with part decomposition. Through qualitative and quantitative evaluations on public datasets, we show that our method achieves good performance in part-wise single-view reconstruction.     

Symmetry-seeking models and 3D object reconstruction

We propose models of 3D shape which may be viewed as deformable bodies composed of simulated elastic material. In contrast to traditional, purely geometric models of shape, deformable models are active—their shapes change in response to externally applied forces. We develop a deformable model for 3D shape which has a preference for axial symmetry. Symmetry is represented even though the model does not belong to a parametric shape family such as (generalized) cylinders. Rather, a symmetry-seeking property is designed into internal forces that constrain the deformations of the model. We develop a framework for 3D object reconstruction based on symmetry-seeking models. Instances of these models are formed from monocular image data through the action of external forces derived from the data. The forces proposed in this paper deform the model in space so that the shape of its projection into the image plane is consistent with the 2D silhouette of an object of interest. The effectiveness of our approach is demonstrated using natural images.     

Optical simulation for cross‐talk evaluation and improvement of autostereoscopic 3‐D displays with a projector array

Abstract— Multi‐view spatial‐multiplexed autostereoscopic 3‐D displays normally use a 2‐D image source and divide the pixels to generate perspective images. Due to the reduction in the resolution of each perspective image for a large view number, a super‐high‐resolution 2‐D image source is required to achieve 3‐D image quality close to the standard of natural vision. This paper proposes an approach by tiling multiple projection images with a low magnification ratio from a microdisplay to resolve the resolution issue. Placing a lenticular array in front of the tiled projection image can lead to an autostereoscopic display. Image distortion and cross‐talk issues resulting from the projection lens and pixel structure of the microdisplay have been addressed with proper selection of the active pixel and adequate pixel grouping and masking. Optical simulation has shown that a 37‐in. 12‐view autostereoscopic display with a full‐HD (1920 × 1080) resolution can be achieved with the proposed 3‐D architecture.     

基于色彩空间分块匹配的三维动画融合技术

为了提高影视动画制作的三维图像成像质量,需要进行动画图像的动态信息融合处理,提出一种基于二维色彩空间分块匹配的三维动画图像的动态信息融合处理技术,采用虚拟视景重构技术进行三维动画图像采集和特征投影处理,对三维动画图像进行二值拟合和边缘轮廓检测,采用RGB分解技术进行三维动画图像的颜色分量提取,采用颜色模板空间投影算法进行三维动画图像的分块融合处理,提高三维动画图像的边缘像素点的特征配对性能,结合三维动画图像的色彩空间分块融合结果进行像素特征优化配置,计算匹配窗口相关系数,实现三维动画图像的动态信息融合处理。仿真结果表明,采用该方法进行三维动画图像的动态信息融合处理,能提高图像输出峰值信噪比,提高动态成像质量。