使用范围数据的三维物体的识别

本文所使用的系统有二个工作阶段。在知识阶段,含有单个物体的景物每次一个地示给系统,景物的范围数据可利用范围测距仪获得。根据区域特性和各区域间的关系建立每一景物的描述并将这种描述存储作为物体的模型。在识别阶段,以与知识阶段同样的方式对未知景物的特征进行描述,然后把这一描述和物体模型匹配,结果可实现成堆物体按顺序地逐个识别。为提高匹配效率,可把数据驱动和模型驱动搜索过程紧密结合。实验结果表明,这一方法是很有希望的。     

显微图象中目标对象的识别

研究了显微图象中目标对象的识别问题。首先比较了显微图象和宏观图象之间的区别,总结了大部分显微图象具有的一般特征,讨论了宏观图象处理方法用于显微图象时存在的缺陷。然后提出了一种目标对象识别的新方法,该方法利用最优颜色通道识别显微图象中的目标对象,动态地调节识别阈值,减少了误识别象素的数量。对残存的误识别象素和脏点象素采用面积滤波的方式去除,进一步提高识别的效果。该文通过实验,识别了几种显微图象中的目标对象,实验发现,使用这一方法不仅能够提取背景中的目标对象,还可以大量减少误识别象素和脏点象素,说明该方法用于显微图象中目标对象的识别具有一定的优点。     

Efficient Detection and Recognition of 3D Ears

The use of ear shape as a biometric trait is a recent trend in research. However, fast and accurate detection and recognition of the ear are very challenging because of its complex geometry. In this work, a very fast 2D AdaBoost detector is combined with fast 3D local feature matching and fine matching via an Iterative Closest Point (ICP) algorithm to obtain a complete, robust and fully automatic system with a good balance between speed and accuracy. Ear images are detected from 2D profile images using the proposed Cascaded AdaBoost detector. The corresponding 3D ear data is then extracted from the co-registered range image and represented with local 3D features. Unlike previous approaches, local features are used to construct a rejection classifier, to extract a minimal region with feature-rich data points and finally, to compute the initial transformation for matching with the ICP algorithm. The proposed system provides a detection rate of 99.9% and an identification rate of 95.4% on Collection F of the UND database. On a Core 2 Quad 9550, 2.83 GHz machine, it takes around 7.7 ms to detect an ear from a 640×480 image. Extracting features from an ear takes 22.2 sec and matching it with a gallery using only the local features takes 0.06 sec while using the full matching including ICP requires 2.28 sec on average.     

基于形态图表示的三维物体识别算法

基于形态图表示的三维物体识别的基本思路是：首先建立待识别物体的模型库,找出模型集中所有模型物体的形态图和特征视图,并提取以它们的拓扑结构信息和几何信息;其次对物体真实图像作轮廓提取和0边界跟踪,得到二维图像的线架图,同时提取出它的拓扑结构信息和几何信息;最后将物体图像的拓扑结构信息和几何信息与模型库中模型物体的拓扑结构信息和几何信息匹配,从而达到识别的目的。文中提出了在生成线图链码时提取其拓扑结构信息和几何信息的方法,由拓扑结构信息和几何信息构造特征矩阵的方法,以及识别过程中特征矩阵的匹配算法。     

Invariant-Based Recognition of Complex Curved 3D Objects from Image Contours

This paper addresses the problem of recognizing three-dimensional objects bounded by smooth curved surfaces from image contours found in a single photograph. The proposed approach is based on a viewpoint-invariant relationship between object geometry and certain image features under weak perspective projection. The image features themselves are viewpoint-dependent. Concretely, the set of all possible silhouette bitangents, along with the contour points sharing the same tangent direction, is the projection of a one-dimensional set of surface points where each point lies on the occluding contour for a five-parameter family of viewpoints. These image features form a one-parameter family of equivalence classes, and it is shown that each class can be characterized by a set of numerical attributes that remain constant across the corresponding five-dimensional set of viewpoints. This is the basis for describing objects by “invariant” curves embedded in high-dimensional spaces. Modeling is achieved by moving an object in front of a camera and does not require knowing the object-to-camera transformation; nor does it involve implicit or explicit three-dimensional shape reconstruction. At recognition time, attributes computed from a single image are used to index the model database, and both qualitative and quantitative verification procedures eliminate potential false matches. The approach has been implemented and examples are presented.     

面向移动对象的高效预测范围聚集查询方法

预测范围聚集查询是移动对象数据库中重要的查询类型之一.提出了一种PRA树高效预测范围聚集查询索引,对速度域进行规则划分,根据速度矢量大小将移动对象映射到不同的速度桶中,针对每个速度桶,提出了一种聚集TPR树索引,通过在TPR树中间节点中加入聚集信息以减少预测范围聚集查询所需要的节点访问代价.PRA树索引增加了一个建于叶节点之上的Hash辅助索引结构,并采用自底向上的删除搜索算法,具有很好的动态性能和并发性.提出了一种增强预测范围聚集查询EPRA算法,采用更精确的剪枝搜索准则,减少了查询所需要访问的节点代价.实验结果与分析表明,基于PRA树索引的EPRA查询算法具有良好的查询性能,优于通用的TPR*树索引.     

三维工业物体的多重描述与识别处理

提出了一种三维工业物体的多重描述与识别方法。在描述中采用了整体形状描述，基元属性描述和关系描述相结合的多重描述策略；在识别过程中，首先根据物体的整体描述产生关于物体身份的初步假设，然后提出三种修剪算法，充分利用关系数据结构的多重约束作为知识启发来修剪搜索树，最后根据距离测度函数实现精匹配。实验验证了上述处理的正确性和一般性。     

Least Committed Splines in 3D Modelling of Free Form Objects from Intensity Images

Generating 3D models of objects from video sequences is an important problem in many multimedia applications ranging from teleconferencing to virtual reality. In this paper, we present a method of estimating the 3D face model from a monocular image sequence, using a few standard results from the affine camera geometry literature in computer vision, and spline fitting techniques using a modified non parametric regression technique. We use the bicubic spline functions to model the depth map, given a set of observation depth maps computed from frame pairs in a video sequence. The minimal number of splines are chosen on the basis of the Schwartz's Criterion. We extend the spline fitting algorithm to hierarchical splines. Note that the camera calibration parameters and the prior knowledge of the object shape is not required by the algorithm. The system has been successfully demonstrated to extract 3D face structure of humans as well as other objects, starting from their image sequences.     

遥感图像三维目标多视点建模识别方法

研究利用遥感灰度图像识别三维目标时的问题,提出一种基于多视点模型的匹配识别方法。使用3D广义锥模型投影得到二维视面模型,用于描述不同视点下的目标视面,并用几何结构特征来检索模型库。匹配过程层次地使用全局的与局部的、统计的与结构的目标识别特征,分为检索和精确匹配两个步骤完成。通过实验验证了该方法的有效性。     

飞行目标红外多光谱高效识别算法

随着新型诱饵的快速发展,在日益复杂的目标环境中探测识别真假目标是红外探测识别系统最难解决的技术问题之一.通过分析天空背景下红外小目标,干扰物,噪音及背景的光谱特性,利用人造飞行目标光谱辐射强度高且相邻波段光谱辐射强度连续性特点,提出了一种以多光谱辐射强度和梯度相组合的目标识别高效算法.就此给出了相应的仿真算例,验证了算法在获取的红外图像信噪比很低,背景高亮度,多个诱饵干扰的条件下也能准确识别目标,具有更强的自适应性,更高的识别率和更为快捷的处理能力.     

Real-time Object Recognition in Sparse Range Images Using Error Surface Embedding

This article formulates a near-lighting shape-from-shading problem with a pinhole camera (perspective projection) and presents a solution to reconstruct the Lambertian surface of bones using a sequence of overlapped endoscopic images, with partial boundaries in each image. First we extend the shape-from-shading problem to deal with perspective projection and near point light sources that are not co-located with the camera center. Secondly we propose a multi-image framework which can align partial shapes obtained from different images in the world coordinates by tracking the endoscope. An iterative closest point (ICP) algorithm is used to improve the matching and recover complete occluding boundaries of the bone. Finally, a complete and consistent shape is obtained by simultaneously re-growing the surface normals and depths in all views. In order to fulfill our shape-from-shading algorithm, we also calibrate both geometry and photometry for an oblique-viewing endoscope that are not well addressed before in the previous literatures. We demonstrate the accuracy of our technique using simulations and experiments with artificial bones.     

一种高效的移动对象连续多范围查询处理框架

针对连续多范围查询处理,结合多核多线程技术和大容量内存技术,通过将移动对象和查询放在内存中处理,提出了一种基于多线程的连续多范围查询处理框架.该框架基于多核处理器平台采用多线程技术周期性地处理查询和移动对象的更新,并周期性地计算多范围查询的结果.提出了基于移动对象数据均匀划分的多线程连续多范围查询处理算法,该算法以为查询建立的格网索引为基础.给出了该索引的构建思想和更新算法.考虑到基于内存的算法受Cache访问性能影响,提出了基于空间填充曲线的移动对象存储优化方法.实验证明,基于多核平台的多线程处理能够高效地处理连续多范围查询,同时通过移动对象存储优化能够提高算法运行中Cache访问命中率,进而提高算法性能.     

Line Extraction in 2D Range Images for Mobile Robotics

This paper presents a geometrical feature detection framework for use with conventional 2D laser rangefinders. This framework is composed of three main procedures: data pre-processing, breakpoint detection and line extraction. In data pre-processing, low-level data organization and processing are discussed, with emphasis to sensor bias compensation. Breakpoint detection allows to determine sequences of measurements which are not interrupted by scanning surface changing. Two breakpoint detectors are investigated, one based on adaptive thresholding, and the other on Kalman filtering. Implementation and tuning of both detectors are also investigated. Line extraction is performed to each continuous scan sequence in a range image by applying line kernels. We have investigated two classic kernels, commonly used in mobile robots, and our Split-and-Merge Fuzzy (SMF) line extractor. SMF employs fuzzy clustering in a split-and-merge framework without the need to guess the number of clusters. Qualitative and quantitative comparisons using simulated and real images illustrate the main characteristics of the framework when using different methods for breakpoint and line detection. These comparisons illustrate the characteristics of each estimator, which can be exploited according to the platform computing power and the application accuracy requirements.     

Probabilistic Modeling and Recognition of 3-D Objects

This paper introduces a uniform statistical framework for both 3-D and 2-D object recognition using intensity images as input data. The theoretical part provides a mathematical tool for stochastic modeling. The algorithmic part introduces methods for automatic model generation, localization, and recognition of objects. 2-D images are used for learning the statistical appearance of 3-D objects; both the depth information and the matching between image and model features are missing for model generation. The implied incomplete data estimation problem is solved by the Expectation Maximization algorithm. This leads to a novel class of algorithms for automatic model generation from projections. The estimation of pose parameters corresponds to a non-linear maximum likelihood estimation problem which is solved by a global optimization procedure. Classification is done by the Bayesian decision rule. This work includes the experimental evaluation of the various facets of the presented approach. An empirical evaluation of learning algorithms and the comparison of different pose estimation algorithms show the feasibility of the proposed probabilistic framework.     

Curve and Surface Duals and the Recognition of Curved 3D Objects from their Silhouettes

This article addresses the problem of recognizing a solid bounded by a smooth surface in a single image. The proposed approach is based on a new representation for two- and three-dimensional shapes, called their signature, that exploits the close relationship between the dual of a surface and the dual of its silhouette in weak-perspective images. Objects are modeled by rotating them in front of a camera without any knowledge of or constraints on their motion. The signatures of their silhouettes are concatenated into a single object signature. To recognize an object from novel viewpoint other than those used during modeling, the signature of the contours extracted from a test photograph is matched to the signatures of all modeled objects signatures. This approach has been implemented, and recognition examples are presented.     

Contextual Part Analogies in 3D Objects

In this paper we address the problem of finding analogies between parts of 3D objects. By partitioning an object into meaningful parts and finding analogous parts in other objects, not necessarily of the same type, many analysis and modeling tasks could be enhanced. For instance, partial match queries can be formulated, annotation of parts in objects can be utilized, and modeling-by-parts applications could be supported. We define a similarity measure between two parts based not only on their local signatures and geometry, but also on their context within the shape to which they belong. In our approach, all objects are hierarchically segmented (e.g. using the shape diameter function), and each part is given a local signature. However, to find corresponding parts in other objects we use a context enhanced part-in-whole matching. Our matching function is based on bi-partite graph matching and is computed using a flow algorithm which takes into account both local geometrical features and the partitioning hierarchy. We present results on finding part analogies among numerous objects from shape repositories, and demonstrate sub-part queries using an implementation of a simple search and retrieval application. We also demonstrate a simple annotation tool that carries textual tags of object parts from one model to many others using analogies, laying a basis for semantic text based search.     

Modeling Close Packing of 3D Objects

The paper represents the concept of Φ-functions and quasi Φ-functions as an efficient tool for mathematical modeling of three-dimensional packing problems for convex geometrical objects with continuous translations and rotations. A mathematical model of close packing of convex geometrical objects is formulated and its basic properties are considered. A solution method is proposed, which includes the following stages: constructing initial points, computing local extrema, and passing from one local minimum to another. The solution approach is efficient to solve optimization packing problems. Numerical examples are given.     

基于图像的树类物体的三维重建

树类物体的三维重建一直是人们很感兴趣的一个研究内容。该文利用基于图像的建模技术,实现了一个从双视点图像重建树木三维模型的系统,提出了一个自动获取树木二维主干骨架的方案,实现了二维骨架点的对应关系求解,三维骨架点的重建、简化及树表面网格的生成。实验结果表明该文提出的方法确实可行、有效。     

PWP3D: Real-Time Segmentation and Tracking of 3D Objects

We formulate a probabilistic framework for simultaneous region-based 2D segmentation and 2D to 3D pose tracking, using a known 3D model. Given such a model, we aim to maximise the discrimination between statistical foreground and background appearance models, via direct optimisation of the 3D pose parameters. The foreground region is delineated by the zero-level-set of a signed distance embedding function, and we define an energy over this region and its immediate background surroundings based on pixel-wise posterior membership probabilities (as opposed to likelihoods). We derive the differentials of this energy with respect to the pose parameters of the 3D object, meaning we can conduct a search for the correct pose using standard gradient-based non-linear minimisation techniques. We propose novel enhancements at the pixel level based on temporal consistency and improved online appearance model adaptation. Furthermore, straightforward extensions of our method lead to multi-camera and multi-object tracking as part of the same framework. The parallel nature of much of the processing in our algorithm means it is amenable to GPU acceleration, and we give details of our real-time implementation, which we use to generate experimental results on both real and artificial video sequences, with a number of 3D models. These experiments demonstrate the benefit of using pixel-wise posteriors rather than likelihoods, and showcase the qualities, such as robustness to occlusions and motion blur (and also some failure modes), of our tracker.     

基于切片图像的三维声纳目标识别

研究了为水下机器人声视觉设计的一套三维成像声纳系统的目标识别方法,该声纳可以在一次发射中获取一系列二维切片图像。根据面阵水平、垂直分辨率的不同和图像中目标的切片数量,结合水声环境对水下成像的影响,分析了几种不同目标切片图像的特点,提出一种以直方图中目标能量为特征的识别方法,该方法在算法实现上避免了三维重建的步骤,使识别速度显著提高,在对水池数据和海试数据的分类识别试验中证明其能有效地识别水下目标。