Determining pose of 3D objects with curved surfaces

A method is presented for computing the pose of rigid 3D objects with arbitrary curved surfaces. Given an input image and a candidate object model and aspect, the method will verify whether or not the object is present and if so, report pose parameters. The curvature method of Bash and Ullman is used to model points on the object rim, while stereo matching is used for internal edge points. The model allows an object edge-map to be predicted from pose parameters. Pose is computed via an iterative search for the best pose parameters. Heuristics are used so that matching can succeed in the presence of occlusion and artifact and without resetting to use of corresponding salient feature points. Bench tests and simulations show that the method almost always converges to ground truth pose parameters for a variety of objects and for a broad set of starting parameters in the same aspect     

Silhouette-based isolated object recognition through curvaturescale space

A complete, fast and practical isolated object recognition system has been developed which is very robust with respect to scale, position and orientation changes of the objects as well as noise and local deformations of shape (due to perspective projection, segmentation errors and non-rigid material used in some objects). The system has been tested on a wide variety of three-dimensional objects with different shapes and material and surface properties. A light-box setup is used to obtain silhouette images which are segmented to obtain the physical boundaries of the objects which are classified as either convex or concave. Convex curves are recognized using their four high-scale curvature extrema points. Curvature scale space (CSS) representations are computed for concave curves. The CSS representation is a multi-scale organization of the natural, invariant features of a curve (curvature zero-crossings or extrema) and useful for very reliable recognition of the correct model since it places no constraints on the shape of objects. A three-stage, coarse-to-fine matching algorithm prunes the search space in stage one by applying the CSS aspect ratio test. The maxima of contours in CSS representations of the surviving models are used for fast CSS matching in stage two. Finally, stage three verifies the best match and resolves any ambiguities by determining the distance between the image and model curves. Transformation parameter optimization is then used to find the best fit of the input object to the correct model     

Exploiting parallelism in 3-D object recognition using the connection machine

This paper addresses the problem of parallelism in 3-D object recognition and localization using a fine-grained SIMD architecture such as the Connection Machine^TM. The input images of partially occluding three-dimensional objects. The objects are made up of piecewise compositions of curved surfaces. The surfaces of interest are cylindrical, conical and spherical surfaces since they cover a large portion of objects encountered in an industrial environment. Qualitative classification of surfaces based on the signs of the Mean and Gaussian curvature is used to come up with Dihedral feature junctions. Dihedral feature junctions are shown to be robust to occlusion and offer a viewpoint independent scheme for modeling the object models and are well suited for matching and pose determination. Hough clustering is chosen as the constraint propagation mechanism on account of the ease of parallelization. Issues regarding parallelism on the Connection Machine^TM for every stage of the recognition and localization process such as segmentations, feature extraction matching and pose determination are discussed. Experimental results on the Connection Machine^TM bring out the advantages of exploiting parallelism for 3-D object recognition and localization on a fine-grained SIMD architecture.     

Cyclic motion detection for motion based recognition

The motion of a walking person is analyzed by examining cycles in the movement. Cycles are detected using autocorrelation and Fourier transform techniques of the smoothed spatio-temporal curvature function of trajectories created by specific points on the object as it performs cyclic motion. A large impulse in the Fourier magnitude plot indicates the frequency at which cycles are occurring. Both synthetically generated and real walking sequences are analyzed for cyclic motion. The real sequences are then used in a motion based recognition application in which one complete cycle is stored as a model, and a matching process is performed using one cycle of an input trajectory.     

基于单幅图像确定目标空间方位新方法的测距系统

提出了一种新的由单幅二维投影图像确定目标三维空间方位的的方法,即在照、摄象机内部参数未知的条件下,采用目标上共面四线与他们在二维图像上投影相匹配的策略,来实现目标的定位;并将其应用于测距系统。因此该方法与以前方法相比,更附和实际需要,从而具有广泛的实际应用推广价值。     

On using CAD models to compute the pose of curved 3D objects

A new approach is presented for explicitly relating image observables to models of curved three-dimensional objects. This relationship is used for object recognition and positioning. Object models consist of collections of parametric surface patches. The image observables considered are raw range data, surface normal and Gaussian curvature, raw image intensity and intensity gradient, raw image contours, and contour orientation and curvature. Elimination theory provides a method for constructing an implicit equation that relates these observables to the three-dimensional position and orientation of object models. Determining the unknown pose parameters is reduced to a fitting problem between the implicit equation and the observed data points. By considering translation-independent observables such as surface normal and curvature, this process is further decomposed into first determining orientation and then determining translation. Applications to object recognition are described, and an implementation is presented.     

基于约束关系的平面立体三维重建

提出一种基于约束的平面立体三维重建算法。该算法采用参数化方式来表示空间直线及其投影,这种参数化方式能满足数字图像中直线提取所需的唯一性、有界性及均匀性条件。依据平面立体投影线图的拓扑结构隐含的三维信息,建立平面立体上棱线、表面空间位置参数之间的约束方程,联立约束方程组求其最小二乘解,恢复出平面立体的三维结构。研究成果可用于计算机视觉和智能CAD系统。     

具有相切面的曲面立体线画图标记研究

为了更好地理解三维景物，介绍了前人对线画图标记的研究成果，同时建立了一种标记具有相切面的曲面立体线画图的方法，并给出了具有相切面的曲面立体线画图的标记规则。由于线画图中的节点是由三面角构成的顶点的投影，因此对于画出隐藏线的具有相切面的曲面立体线画图，其合法的节点标记形式有38种，其中Y型节点有6种，W型节点有18种，V型节点有14种。新的标记方法适用于由平面立体和曲面立体组合而成的复杂立体线画图。     

Algorithms for optimal partial matching of free-form objects with scaling effects

A free-form object matching problem is addressed in this paper. Two methods are proposed to solve a partial matching problem with scaling effects and no prior information on correspondence or the rigid body transformation involved. The first method uses umbilical points, which behave as fingerprints of a surface and their qualitative properties can be used for matching purposes. The second method uses an optimization scheme based on the extension of the KH curvature matching method [Comput. Aided Design 35 (2003) 913], first introduced in the context of a matching problem without scaling effects. Two types of curvatures, the Gaussian and the mean curvatures, are used to establish correspondences between two objects. The curvature matching method is formulated in terms of minimization of an objective function depending on the unknown scaling factor, and the rigid body transformation parameters. The accuracy and complexity of the proposed methods as well as the convergence for the optimization approach are analyzed. Examples illustrate the two methods.     

基于点线关系从透视画隐线图重构三维平面立体

提出了一种基于点与直线关系从透视投影画隐线图建立平面立体线框模型的新方法。给出了基于点线关系的基本约束,根据透视投影画隐线图中隐含的点与直线位置关系建立约束方程,建立一个线性系统,通过求解该线性系统得到平面立体的三维信息。用算例进行验证,得到了平面立体的三维信息。     

双目主动视觉监测平台下的目标识别

利用对目标旋转、尺度变化、视角变化等具有稳定性的尺度不变特征变换(SIFT)算法,提出一种适用于基于圆轨的基线可调双目主动视觉监测平台的目标识别方法,通过离线建立物体的多侧面SIFT特征点数据库,将三维空间的目标转换为二维特征描述,利用二维特征描述实现三维空间目标的识别,以提高匹配识别效率。实验结果表明,该方法能实时准确地识别目标。     

基于模板替换的室内场景建模方法研究

当前,室内场景建模相关研究已经取得很多进展,特别是基于多视角融合的建模 框架与基于单视角的建模框架的提出,增强了机器人的环境感知能力。但仍然存在以下不足： ①基于多视角融合的建模方式预处理时间长,建模完成后需线下优化过程,不能满足特定条件 下的建模需求;②基于单视角的建模算法输出一般为体素,建模质量较低,信息缺失严重,对 于场景细节无法精确刻画,难以满足机器人交互的要求。特提出一种基于模板替换的室内场景 建模方法研究。首先,预处理由设备采集到的三维点云场景,分割出存在点云缺失的单个对象, 并利用虚拟扫描技术采样对象表面点并计算法向量与曲率。采用八叉树网格结构,将点云的法 向量与曲率信息分别存入网格中,再利用卷积神经网络(CNN)提取高维特征向量,将其与数据 库中三维对象特征进行欧氏距离比较,得到检索序列。从序列中挑选出最相似的对象,利用迭 代就近点(ICP)配准方法,与扫描场景进行配准,完成场景优化。对提出的网络模型在 2 个基准 数据集上进行测试并表现出良好的性能。     

Computer Graphics System for Reproducing Three- Dimensional Shape from Idea Sketch

This paper describes the technical features and method of implementation of our designer support system which enables reproducing a three-dimensional shape from an idea sketch speedily and modifying the reproduced shape easily, thereby facilitating the consistency of the shape to be checked from a design viewpoint. The designer support system was developed as a tool to cut the time and labor designers have to spend in the design process and help designers to fully display their creativity–the essential attribute of designers. This system uses cross-section lines of an idea sketch of an object drawn by an industrial designer as input data to reproduce automatically a three-dimensional wireframe model of the object by a newly developed three-dimensional graphic algorithm including graphic constraints. In addition, it automatically creates planes by scanning the area enclosed by reproduced curved lines and subjects them to shading. In this process, the dimensions of the object need not be input to the system. The designer can operate the system simply by using the mouse to input appropriate data. Thus, the system permits the designer to easily express his idea in the form of a three-dimensional shape and study idea variations on the display screen without creating a mockup.     

基于三次样条函数的传感器特性曲面二维插值

在传感器输出、输入和环境参量均存在非线性的情况下,传统校准方法遇到困难,为提供一种提高测量精度的新途径,在接受非线性事实的基础上,采用三次样条函数二维插值,建立起传感器传递特性曲面.通过实例计算显示了一个化学传感器特性曲面.所获得的传感器特性曲面光滑性好,在输入和环境参量2个方向的一阶、二阶导数都连续,更符合传感器实际传递特性.     

基于Fisher分类和空间映射的分形图像编码方法

针对Fisher分类分形图像压缩算法中二维灰度变换匹配性能较差的问题,提出了改进的空间映射灰度变换方法。该方法将位置与亮度同时纳入到灰度变换中,形成三维空间上曲面模式之间的线性映射,并预先量化空间映射压缩因子,再计算和量化空间映射灰度变换的其他系数,提高range块和domain块成功匹配的可能性。实验证明,该方法在不降低重构图像质量的前提下,减少了编码块数,提高了图像的压缩比,大幅缩短了编码时间。     

On recognizing and positioning curved 3-D objects from imagecontours

An approach for explicitly relating the shape of image contours to models of curved three-dimensional objects is presented. This relationship is used for object recognition and positioning. Object models consist of collections of parametric surface patches and their intersection curves; this includes nearly all representations used in computer-aided geometric design and computer vision. The image contours considered are the projections of surface discontinuities and occluding contours. Elimination theory provides a method for constructing the implicit equation of these contours for an object observed under orthographic or perspective projection. This equation is parameterized by the object's position and orientation with respect to the observer. Determining these parameters is reduced to a fitting problem between the theoretical contour and the observed data points. The proposed approach readily extends to parameterized models. It has been implemented for a simple world composed of various surfaces of revolution and tested on several real images     

Matching wire frame objects from their two dimensional perspective projections

A wire frame object consists of a set of three dimensional arcs, each arc being a sequence of conics and line segments lying in the same plane, with different arcs being allowed to lie on different planes. Given a picture taken by a camera focusing on one wire frame object, we show how to determine what the object is and where it is situated relative to the camera when the camera viewing parameters are unknown.

To accomplish the object identification, we begin with a segmented picture. Then we construct a ray from the lens to each point on the boundary of every region. For each region, the collection of its associated rays is a cone. We show that by constructing cones, the two-dimensional to three-dimensional matching problem is transformed into an equivalent three-dimensional to three-dimensional matching problem.

This matching problem is expressed as a nonlinear optimization search procedure on the 6 camera viewing parameters: the 3 translation parameters and the 3 rotation parameters. A solution is found when a viewing position and optical axis is determined which is consistent with the world knowledge we have of possible curves and the observed image data.     

Fabrication of curved copper micromesh sheets using flexible PDMS molds

A unique fabrication method for a curved copper micromesh is proposed and demonstrated. A PDMS mold was fabricated using a microcasting process and then used as a flexible mold in copper electroplating. The fabricated copper micromesh was well formed and connected without any cracks within the entire mold area. The experimental results verified that the fabricated features of the copper micromesh accurately followed the shape of the microstructures and the curvature of the PDMS mold. This unique fabrication method provides an alternative means to produce curved or three-dimensional metal microstructures.