Multiview registration of 3D scenes by minimizing error between coordinate frames

This paper addresses the problem of large-scale multiview registration of range images captured from unknown viewing directions. To reduce the computational burden, we separate the local problem of pairwise registration on neighboring views from the global problem of distribution of accumulated errors. We define the global problem as an optimization over the graph of neighboring views, and we show how the graph can be decomposed into a set of cycles such that the optimal transformation parameters for each cycle can be solved in closed form. We then describe an iterative procedure that can be used to integrate the solutions for the set of cycles across the graph of views. This method for error distribution does not require point correspondences between views, and can be used to integrate any method of pairwise registration or robot odometry.     

Semi‐isometric Registration of Line Features for Flexible Fitting of Protein Structures

In this paper, we study a registration problem that is motivated by a practical biology problem – fitting protein structures to low‐re solution density maps. We consider registration between two sets of lines features (e.g., helices in the proteins) that have undergone not a single, but multiple isometric transformations (e.g., hinge‐motions). The problem is further complicated by the presence of symmetry in each set. We formulate the problem as a clique‐finding problem in a product graph, and propose a heuristic solution that includes a fast clique‐finding algorithm unique to the structure of this graph. When tested on a suite of real protein structures, the algorithm achieved high accuracy even for very large inputs containing hundreds of helices.     

Towards a general multi-view registration technique

We present an algorithm that reduces significantly the level of the registration errors between all pairs in a set of range views. This algorithm refines initial estimates of the transformation matrices obtained from either the calibrated acquisition setup or a crude manual alignment. It is an instance of a category of registration algorithms known as iterated closest-point (ICP) algorithms. The algorithm considers the network of views as a whole and minimizes the registration errors of all views simultaneously. This leads to a well-balanced network of views in which the registration errors are equally distributed, an objective not met by previously published ICP algorithms which all process the views sequentially. Experimental results show that this refinement technique improves the calibrated registrations and the quality of the integrated model for complex multi-part objects. In the case of scenes comprising man-made objects of very simple shapes, the basic algorithm faces problems common to all ICP algorithms and so must be extended     

A Multi-agent Architecture Based on the BDI Model for Data Fusion in Visual Sensor Networks

The newest surveillance applications is attempting more complex tasks such as the analysis of the behavior of individuals and crowds. These complex tasks may use a distributed visual sensor network in order to gain coverage and exploit the inherent redundancy of the overlapped field of views. This article, presents a Multi-agent architecture based on the Belief-Desire-Intention (BDI) model for processing the information and fusing the data in a distributed visual sensor network. Instead of exchanging raw images between the agents involved in the visual network, local signal processing is performed and only the key observed features are shared. After a registration or calibration phase, the proposed architecture performs tracking, data fusion and coordination. Using the proposed Multi-agent architecture, we focus on the means of fusing the estimated positions on the ground plane from different agents which are applied to the same object. This fusion process is used for two different purposes: (1) to obtain a continuity in the tracking along the field of view of the cameras involved in the distributed network, (2) to improve the quality of the tracking by means of data fusion techniques, and by discarding non reliable sensors. Experimental results on two different scenarios show that the designed architecture can successfully track an object even when occlusions or sensor??s errors take place. The sensor??s errors are reduced by exploiting the inherent redundancy of a visual sensor network with overlapped field of views.     

Aspect graphs for three‐dimensional object recognition machine vision systems

The purpose of this research is to seek evidence for viewer‐centered (especially aspect‐graph‐based) visual processing in the elementary task of object understanding. Two homologous, bilaterally symmetrical three‐dimensional (3‐D) objects have been employed that differ in that one is based on parts with flat surfaces and the other on parts with curved surfaces. The following procedure has been followed, separately for each object. In the training (saturated free inspection and manipulation) phase, a location (identical for both objects) of the object is marked with a red strip and the subjects' task is to memorize the object structure as well as the position of the strip. In the test phase, two‐dimensional views of the object without the strip are presented and the subjects' task is to determine whether the previously marked location should be visible or invisible in the particular view. Findings have been found consistent with an aspect‐graph‐based 3‐D object representation: (a) the reaction times and errors show characteristic dependencies on viewpoint; (b) a number of views (corresponding to certain aspects and aspect transitions of the aspect graph) consistently produce faster and more accurate recognition; (c) the differences in the aspect graphs of the two objects are reflected in differing patterns of reaction times and errors; furthermore; (d) the subjects impose a standard orientation on the objects, whereby a strong inversion effect is observed; and (e) performance varies in a similar way for both objects as a function of tilt. It is concluded that object understanding is viewpoint dependent, that is, based on a number of views. The characteristics of the views found to be most important for object understanding can be employed for creating efficient 3‐D object recognition machine vision systems. © 2005 Wiley Periodicals, Inc. Int J Int Syst 20: 47–72, 2005.     

TreeMatrix: A Hybrid Visualization of Compound Graphs

We present a hybrid visualization technique for compound graphs (i.e. networks with a hierarchical clustering defined on the nodes) that combines the use of adjacency matrices, node‐link and arc diagrams to show the graph, and also combines the use of nested inclusion and icicle diagrams to show the hierarchical clustering. The graph visualized with our technique may have edges that are weighted and/or directed. We first explore the design space of visualizations of compound graphs and present a taxonomy of hybrid visualization techniques. We then present our prototype, which allows clusters (i.e. subtrees) of nodes to be grouped into matrices or split apart using a radial menu. We also demonstrate how our prototype can be used in the software engineering domain, and compare it to the commercial matrix‐based visualization tool Lattix using a qualitative user study.     

Using structured steiner trees for hierarchical global routing

The Steiner problem in a hierarchical graph model, the structured graph, is defined. The problem finds applications to hierarchical global routing. Properties of minimum-cost Steiner trees in structured graphs are investigated. A “top-down” approximate solution to the Steiner problem in structured graphs, called a top-down Steiner tree, is defined, and an algorithm is given to compute such solution. The top-down Steiner tree provides also an approximate solution to the Steiner problem in graphs admitting a structured representation. The properties of such solution are discussed and some experimental results on the quality of the approximation are presented. A reduction in time complexity is demonstrated with respect to both exact and heuristic algorithms applied to such graphs.     

Consistent integration of models based on views of meta models

The complexity of large system models in software engineering nowadays is mastered by using different views. View-based modelling aims at creating small, partial models, each one of them describing some aspect of the system. Existing formal techniques supporting view-based visual modelling are based on typed attributed graphs, where views are related by typed attributed graph morphisms. Such morphisms up to now require a meta model given by a fixed type graph, as well as a fixed data signature and domain. This is in general not adequate for view-oriented modeling where only parts of the complete meta model are known and necessary when modelling a partial view of the system. The aim of this paper is to extend the framework of typed attributed graph morphisms to generalized typed attributed graph morphisms, short GAG-morphisms, which involve changes of the type graph, data signature, and domain. This allows the modeller to formulate type hierarchies and views of visual languages defined by GAG-morphisms between type graphs, short GATG-morphisms. In this paper, we study the interaction and integration of views, and the restriction of views along type hierarchies. In the main result, we present suitable conditions for the integration and decomposition of consistent view models (Theorem 4.1) and extend these conditions to view models defined over meta models with constraints (Theorem 5.1). As a running example, we use a visual domain-specific modelling language to model coarse-grained IT components and their connectors in decentralized IT infrastructures. Using constraints, we formulate connection properties as invariants.     

一种HRG模型初始化算法及在链路预测中的应用

在利用层次随机图(HRG)模型对真实网络进行链路预测的过程中,需要构造一个初始层次随机图来初始化马尔科夫链以运行马尔科夫链蒙特卡洛抽样算法。针对现有的层次随机图初始化方案效率不高的问题,本文对初始层次随机图模型进行重建,提出一种新的层次随机图模型初始化算法。该算法分为2个阶段,第一阶段引入相似性指标(LHN-I指标)为网络中的边进行排序;第二阶段利用排序好的边对层次随机图模型进行构造。在该过程中,设计一种将网络顶点插入到层次随机图模型中的方法。通过3个实例网络对提出的算法与现有算法的性能进行比较,实验结果表明,利用提出的初始化算法构造出的初始层次随机图不仅有着较高的似然值,而且使得马尔科夫链蒙特卡洛算法能够更快地收敛,进而降低链路预测的时间消耗。除此之外,在链路预测实验中,改进的基于层次随机图模型的链路预测算法相比一些基于相似性指标的链路预测算法有着较好的预测精度。     

Symmetry Hierarchy of Man‐Made Objects

We introduce symmetry hierarchy of man‐made objects, a high‐level structural representation of a 3D model providing a symmetry‐induced, hierarchical organization of the model's constituent parts. Given an input mesh, we segment it into primitive parts and build an initial graph which encodes inter‐part symmetries and connectivity relations, as well as self‐symmetries in individual parts. The symmetry hierarchy is constructed from the initial graph via recursive graph contraction which either groups parts by symmetry or assembles connected sets of parts. The order of graph contraction is dictated by a set of precedence rules designed primarily to respect the law of symmetry in perceptual grouping and the principle of compactness of representation. We show that symmetry hierarchy naturally implies a hierarchical segmentation that is more meaningful than those produced by local geometric considerations. We also develop an application of symmetry hierarchies for structural shape editing.     

一种鲁棒的城市复杂动态场景点云配准方法

针对城市道路环境中面临的动态目标繁多、遮挡严重、以及GPS （全球定位系统）误差较大的问题,提出了一种无需检测动态目标且可以适应不同初始位置误差的快速、鲁棒的配准方法.首先,使用区域生长方法对去除地面的障碍物点云进行目标分割,并通过设定约束条件优化分割效果,生成点云的目标重心点集合;然后,提出了一种多层嵌套的RANSAC （随机抽样一致性）算法架构,迭代地更新配准结果,实现重心点集的粗配准并去除外点;最后,利用ICP （迭代最近点）进行点云的精确配准.与传统RANSAC方法的对比实验表明,该方法能够在复杂的动态场景和较大的初始位置误差下完成精确可靠的点云配准,且其配准成功率和配准速度明显高于传统方法.     

Observer‐based leader‐following consensus of uncertain nonlinear multi‐agent systems

In this paper, the leader‐following consensus problem of uncertain high‐order nonlinear multi‐agent systems on directed graph with a fixed topology is studied, where it is assumed that the relative states of a follower and its neighbors are immeasurable and only the relative outputs are available. Nonlinear adaptive observers are firstly proposed for each follower to estimate the states of it and its neighbors, and an observer‐based distributed adaptive control scheme is constructed to guarantee that all followers asymptotically synchronize to a leader with tracking errors being semi‐globally uniform ultimate bounded. On the basis of algebraic graph theory and Lyapunov theory, the closed‐loop system stability analysis is conducted. Finally, numerical simulations are presented to illustrate the effectiveness and potential of the proposed new design techniques. Copyright © 2017 John Wiley & Sons, Ltd.     

基于深度图正则化矩阵分解的多视图聚类算法

针对现实社会中由多种表示或视图组成的多视图数据广泛存在的问题,深度矩阵分解模型因其能够挖掘数据的层次信息而备受关注,但该模型忽略了数据的几何结构信息.为解决以上问题,本文提出基于深度图正则化矩阵分解的多视图聚类算法,通过获取每个视图的局部结构信息和全局结构信息在逐层分解中加入两个图正则化限制,保护多视图数据的几何结构信...     

Optimizing cyclic join view maintenance over distributed data sources

Materialized views defined over distributed data sources are critical for many applications to ensure efficient access, reliable performance, and high availability. Materialized views need to be maintained upon source updates since stale view extents may not serve well or may even mislead user applications. Thus, view maintenance performance is one of the keys to the success of these applications. In this work, we investigate two maintenance strategies, extended batching and view graph transformation, for maintaining general join views where join conditions may exist between any pairs of data sources possibly with cycles. Many choices are available for maintaining cyclic join views. We thus propose a cost-driven view maintenance framework which generates optimized maintenance plans tuned to the environmental settings. The proposed framework has been implemented in the TxnWrap system. Experimental studies illustrate that our proposed optimization techniques significantly improve the view maintenance performance in a distributed environment.     

Robust trajectory tracking control for unmanned tail‐sitters in aggressive flight mode transitions

In this paper, the trajectory tracking control problem is investigated for a new typical tail‐sitter. A robust hierarchical control method is proposed to achieve aggressive flight mode transitions. The proposed control method results in a composite controller including a translational controller and a rotational controller to control the position and attitude respectively. Continuous aggressive flight mode transitions can be achieved without switching on the coordinate systems or the controller structures. It is proven that the tracking errors of the designed closed‐loop system can converge into a given neighborhood of the origin in a finite time. Simulation results show the effectiveness of the proposed control strategy.     

Model‐assisted extended state observer and dynamic surface control–based trajectory tracking for quadrotors via output‐feedback mechanism

In this paper, an output‐feedback trajectory tracking controller for quadrotors is presented by integrating a model‐assisted extended state observer (ESO) with dynamic surface control. The quadrotor dynamics are described by translational and rotational loops with lumped disturbances to promote the hierarchical control design. Then, by exploiting the structural property of the quadrotor, a model information–assisted high‐order ESO that relies only on position measurements is designed to estimate not only the unmeasurable states but also the lumped disturbances in the rotational loop. In addition, to account for the problem of “explosion of complexity” inherent in hierarchical control, the output feedback–based trajectory tracking and attitude stabilization laws are respectively synthesized by utilizing dynamic surface control and the corresponding estimated signals provided by the ESO. The stability analysis is given, showing that the output‐feedback trajectory tracking controller can ensure the ultimate boundedness of all signals in the closed‐loop system and make the tracking errors arbitrarily small. Finally, flight simulations with respect to an 8‐shaped trajectory command are performed to verify the effectiveness of the proposed scheme in obtaining the stable and accurate trajectory tracking using position measurements only.     

Selection of views to materialize in a data warehouse

A data warehouse stores materialized views of data from one or more sources, with the purpose of efficiently implementing decision-support or OLAP queries. One of the most important decisions in designing a data warehouse is the selection of materialized views to be maintained at the warehouse. The goal is to select an appropriate set of views that minimizes total query response time and the cost of maintaining the selected views, given a limited amount of resource, e.g., materialization time, storage space, etc. In This work, we have developed a theoretical framework for the general problem of selection of views in a data warehouse. We present polynomial-time heuristics for a selection of views to optimize total query response time under a disk-space constraint, for some important special cases of the general data warehouse scenario, viz.: 1) an AND view graph, where each query/view has a unique evaluation, e.g., when a multiple-query optimizer can be used to general a global evaluation plan for the queries, and 2) an OR view graph, in which any view can be computed from any one of its related views, e.g., data cubes. We present proofs showing that the algorithms are guaranteed to provide a solution that is fairly close to (within a constant factor ratio of) the optimal solution. We extend our heuristic to the general AND-OR view graphs. Finally, we address in detail the view-selection problem under the maintenance cost constraint and present provably competitive heuristics.     

Object Completion using k‐Sparse Optimization

We present a new method for the completion of partial globally‐symmetric 3D objects, based on the detection of partial and approximate symmetries in the incomplete input dataset. In our approach, symmetry detection is formulated as a constrained sparsity maximization problem, which is solved efficiently using a robust RANSAC‐based optimizer. The detected partial symmetries are then reused iteratively, in order to complete the missing parts of the object. A global error relaxation method minimizes the accumulated alignment errors and a non‐rigid registration approach applies local deformations in order to properly handle approximate symmetry. Unlike previous approaches, our method does not rely on the computation of features, it uniformly handles translational, rotational and reflectional symmetries and can provide plausible object completion results, even on challenging cases, where more than half of the target object is missing. We demonstrate our algorithm in the completion of 3D scans with varying levels of partiality and we show the applicability of our approach in the repair and completion of heavily eroded or incomplete cultural heritage objects.     

Successive refinement of side information for multi-view distributed video coding

Inter-camera registration in multi-view systems with overlapped views has a particularly long and sophisticated research history within the computer vision community. Moreover, when applied to Distributed Video Coding, in systems with at least one moving camera it represents a real challenge due to the necessary data at decoder for generating the side information without any a priori knowledge of each instant camera position. This paper proposes a solution to this problem based on successive multi-view registration and motion compensated extrapolation for on-the-fly re-correlation of two views at decoder. This novel technique for side information generation is codec-independent, robust and flexible with regard to any free motion of the cameras. Furthermore, it doesn’t require any additional information from encoders nor communication between cameras or offline training stage. We also propose a metric for an objective assessment of the multi-view correlation performance.     

Indoor Scene Reconstruction from Sets of Noisy Range Images

This paper describes a system for building 3D models of indoor scenes from sets of noisy laser range images. It addresses several important aspects of this problem, namely, preprocessing, which includes image segmentation and planar model fitting; view registration, which is the method of determining the rigid transformation that describes the relative pose of the camera platform between views; and reconstruction, which is the subsequent integration or fusion of separate range images into a single 3D model. Our proposed strategy is to use a statistical sensor model. We thus account for noise properties of the data at each stage in the reconstruction process, which produces reliable results even in the presence of significant measurement noise. We give an empirical analysis of a plane-based registration method and present results using real range data that demonstrate the performance of the entire reconstruction system.