ChESS - Quick and Robust Detection of Chess-board Features

Localization of chess-board vertices is a common task in computer vision, underpinning many applications, but relatively little work focusses on designing a specific feature detector that is fast, accurate and robust. In this paper the `Chess-board Extraction by Subtraction and Summation' (ChESS) feature detector, designed to exclusively respond to chess-board vertices, is presented. The method proposed is robust against noise, poor lighting and poor contrast, requires no prior knowledge of the extent of the chess-board pattern, is computationally very efficient, and provides a strength measure of detected features. Such a detector has significant application both in the key field of camera calibration, as well as in Structured Light 3D reconstruction. Evidence is presented showing its robustness, accuracy, and efficiency in comparison to other commonly used detectors both under simulation and in experimental 3D reconstruction of flat plate and cylindrical objects

Warping trajectories for video synchronization

Temporal synchronization of multiple video recordings of the same dynamic event is a critical task in many computer vision applications e.g. novel view synthesis and 3D reconstruction. Typically this information is implied, since recordings are made using the same timebase, or time-stamp information is embedded in the video streams. Recordings using consumer grade equipment do not contain this information; hence, there is a need to temporally synchronize signals using the visual information itself. Previous work in this area has either assumed good quality data with relatively simple dynamic content or the availability of precise camera geometry. In this paper, we propose a technique which exploits feature trajectories across views in a novel way, and specifically targets the kind of complex content found in consumer generated sports recordings, without assuming precise knowledge of fundamental matrices or homographies. Our method automatically selects the moving feature points in the two unsynchronized videos whose 2D trajectories can be best related, thereby helping to infer the synchronization index. We evaluate performance using a number of real recordings and show that synchronization can be achieved to within 1 sec, which is better than previous approaches. Copyright 2013 ACM.

ChESS - Quick and robust detection of chess-board features

Localization of chess-board vertices is a common task in computer vision, underpinning many applications, but relatively little work focusses on designing a specific feature detector that is fast, accurate and robust. In this paper the 'Chess-board Extraction by Subtraction and Summation' (ChESS) feature detector, designed to exclusively respond to chess-board vertices, is presented. The method proposed is robust against noise, poor lighting and poor contrast, requires no prior knowledge of the extent of the chess-board pattern, is computationally very efficient, and provides a strength measure of detected features. Such a detector has significant application both in the key field of camera calibration, as well as in structured light 3D reconstruction. Evidence is presented showing its superior robustness, accuracy, and efficiency in comparison to other commonly used detectors, including Harris & Stephens and SUSAN, both under simulation and in experimental 3D reconstruction of flat plate and cylindrical objects. © 2013 Elsevier Inc. All rights reserved.

Achievements and challenges in machine vision-based inspection of large concrete structures

Large concrete structures need to be inspected in order to assess their current physical and functional state, to predict future conditions, to support investment planning and decision making, and to allocate limited maintenance and rehabilitation resources. Current procedures in condition and safety assessment of large concrete structures are performed manually leading to subjective and unreliable results, costly and time-consuming data collection, and safety issues. To address these limitations, automated machine vision-based inspection procedures have increasingly been proposed by the research community. This paper presents current achievements and open challenges in vision-based inspection of large concrete structures. First, the general concept of Building Information Modeling is introduced. Then, vision-based 3D reconstruction and as-built spatial modeling of concrete civil infrastructure are presented. Following that, the focus is set on structural member recognition as well as on concrete damage detection and assessment exemplified for concrete columns. Although some challenges are still under investigation, it can be concluded that vision-based inspection methods have significantly improved over the last 10 years, and now, as-built spatial modeling as well as damage detection and assessment of large concrete structures have the potential to be fully automated.

Synchronization of user-generated videos through trajectory correspondence and a refinement procedure

Temporal synchronization of multiple video recordings of the same dynamic event is a critical task in many computer vision applications e.g. novel view synthesis and 3D reconstruction. Typically this information is implied through the time-stamp information embedded in the video streams. User-generated videos shot using consumer grade equipment do not contain this information; hence, there is a need to temporally synchronize signals using the visual information itself. Previous work in this area has either assumed good quality data with relatively simple dynamic content or the availability of precise camera geometry. Our first contribution is a synchronization technique which tries to establish correspondence between feature trajectories across views in a novel way, and specifically targets the kind of complex content found in consumer generated sports recordings, without assuming precise knowledge of fundamental matrices or homographies. We evaluate performance using a number of real video recordings and show that our method is able to synchronize to within 1 sec, which is significantly better than previous approaches. Our second contribution is a robust and unsupervised view-invariant activity recognition descriptor that exploits recurrence plot theory on spatial tiles. The descriptor is individually shown to better characterize the activities from different views under occlusions than state-of-the-art approaches. We combine this descriptor with our proposed synchronization method and show that it can further refine the synchronization index. © 2013 ACM.

Large depth-of-view portable three-dimensional laser scanner and its segmental calibration for robot vision

A portable 3D laser scanning system has been designed and built for robot vision. By tilting the charge coupled device (CCD) plane of portable 3D scanning system according to the Scheimpflug condition, the depth-of-view is successfully extended from less than 40 to 100 mm. Based on the tilted camera model, the traditional two-step camera calibration method is modified by introducing the angle factor. Meanwhile, a novel segmental calibration approach, i.e., dividing the whole work range into two parts and calibrating, respectively, with corresponding system parameters, is proposed to effectively improve the measurement accuracy of the large depth-of-view 3D laser scanner. In the process of 3D reconstruction, different calibration parameters are used to transform the 2D coordinates into 3D coordinates according to the different positions of the image in the CCD plane, and the measurement accuracy of 60 mu m is obtained experimentally. Finally, the experiment of scanning a lamina by the large depth-of-view portable 3D laser scanner used by an industrial robot IRB 4400 is also employed to demonstrate the effectiveness and high measurement accuracy of our scanning system. (C) 2007 Elsevier Ltd. All rights reserved.

无标定三维重建方法研究

无标定情况下的三维重建技术是近年来计算机视觉领域研究的一个热点问题。它由未标定的图像序列恢复出摄像机的投影矩阵，并重建物体在欧氏空间下的三维结构。该技术在虚拟现实、人机交互、建筑构图、医学成像等方面有着广泛的应用。因此，越来越受到研究者们的重视。 本文主要对在射影空间以及欧氏空间下通过未标定图像进行三维重建的方法进行研究，并取得如下成果： 基础矩阵包含了两幅图像间的几何约束的所有信息，是三维重建的基础和关键。本文分析了多种基础矩阵估计方法，总结了它们的不足，提出了一种基于变量含误差(EV)模型的基础矩阵估计方法。该方法考虑了坐标规范化、秩的约束、目标函数几何意义和测量值误差，实验表明其估计结果具有较高的精度和抗噪性。 为完成三维重建，本文由基础矩阵表示出了欧氏空间下摄像机的投影矩阵，提出了一种基于EV模型确定欧氏投影系数的方法。针对模型中对参数非线性的求解，本文采用最少的参数，将模型转化为二次型的形式，并用伪线性化的方法来求解参数。实验表明，在点的位置误差下，该方法仍具有很高的精度，重建结果较好；在有少数的误匹配特征点的情况下，也完成了重建。 本文设计了增强现实的实验，用本文的方法完成三维重建，并将虚拟物体加入到重建的场景中。实验结果验证了本文方法的可行性和重建的效果。

立体视觉中误匹配滤波方法的研究

从二维空间和三维空间2种角度研究误匹配滤波算法,提出在匹配前用于降低误匹配的灰度预处理算法和一种基于真实控制点的视差滤波算法。前者只针对2幅图像的重叠区域进行灰度均衡,可以减少计算量,后者在传统视差均值滤波的基础上可进一步提高误匹配的滤波效率。基于真实图像的实验结果表明,新算法可以有效滤除误匹配,提高三维重建精度,保证重建效果。

月球机器人仿真中一种消除轮地交互误差的方法

利用虚拟现实技术虚拟出月球机器人在月面上的作业环境和作业过程,是提高机器人作业的安全系数和工作效率的一条有效途径。在3D重建得到的虚拟月面环境中,如果采用通常的单纯基于运动学(或者动力学)模型的仿真方法,对机器人的作业和运动进行虚拟,那么机器人与地形交互的过程中容易产生接触偏差。而且,随着仿真时间的推进,这种接触偏差会逐渐积累并不断增大,进而严重影响仿真测试的精度和效果。为了消除月球机器人仿真中的轮地交互误差,在分析误差来源的基础上,提出了基于运动学优化的解决方法。最后利用实际的虚拟现实仿真系统,验证了所提出方法的有效性。

基于模型的位姿估计中优化方法研究

介绍了基于模型的位姿估计中所使用的一些优化方法。为了提高位姿估计的精度,摄像机的标定参数必须足够精确,这就对标定过程的非线性优化算法提出了很高的要求,采用了一种新的优化目标函数,用来最小化控制点间的三维重建误差,从而使标定参数是全局最优;在双像机位姿估计中,引入了实时遗传算法进行全局搜索,加快了算法的收敛速度。最后的实验证明了这些方法的正确性并显示出这些方法在精度上比传统方法有了较大程度的提高。

Mandelbrot集与Julia集的图象生成算法

介绍一种在计算机上生成Ｍａｎｄｅｌｂｒｏｔ集和Ｊｕｌｉａ集图象的简易算法。该算法对计算机的软硬件要求均不高，在普通的微机以及工作站上均可实现。

Direct Estimation of Motion and Extended Scene Structure from a Moving Stereo Rig

We describe a new method for motion estimation and 3D reconstruction from stereo image sequences obtained by a stereo rig moving through a rigid world. We show that given two stereo pairs one can compute the motion of the stereo rig directly from the image derivatives (spatial and temporal). Correspondences are not required. One can then use the images from both pairs combined to compute a dense depth map. The motion estimates between stereo pairs enable us to combine depth maps from all the pairs in the sequence to form an extended scene reconstruction and we show results from a real image sequence. The motion computation is a linear least squares computation using all the pixels in the image. Areas with little or no contrast are implicitly weighted less so one does not have to explicitly apply a confidence measure.

Automatically Recovering Geometry and Texture from Large Sets of Calibrated Images

Three-dimensional models which contain both geometry and texture have numerous applications such as urban planning, physical simulation, and virtual environments. A major focus of computer vision (and recently graphics) research is the automatic recovery of three-dimensional models from two-dimensional images. After many years of research this goal is yet to be achieved. Most practical modeling systems require substantial human input and unlike automatic systems are not scalable. This thesis presents a novel method for automatically recovering dense surface patches using large sets (1000's) of calibrated images taken from arbitrary positions within the scene. Physical instruments, such as Global Positioning System (GPS), inertial sensors, and inclinometers, are used to estimate the position and orientation of each image. Essentially, the problem is to find corresponding points in each of the images. Once a correspondence has been established, calculating its three-dimensional position is simply a matter of geometry. Long baseline images improve the accuracy. Short baseline images and the large number of images greatly simplifies the correspondence problem. The initial stage of the algorithm is completely local and scales linearly with the number of images. Subsequent stages are global in nature, exploit geometric constraints, and scale quadratically with the complexity of the underlying scene. We describe techniques for: 1) detecting and localizing surface patches; 2) refining camera calibration estimates and rejecting false positive surfels; and 3) grouping surface patches into surfaces and growing the surface along a two-dimensional manifold. We also discuss a method for producing high quality, textured three-dimensional models from these surfaces. Some of the most important characteristics of this approach are that it: 1) uses and refines noisy calibration estimates; 2) compensates for large variations in illumination; 3) tolerates significant soft occlusion (e.g. tree branches); and 4) associates, at a fundamental level, an estimated normal (i.e. no frontal-planar assumption) and texture with each surface patch.

Morphological and ecological studies on the phylum Cycliophora

Cycliophora é um filo animal descrito recentemente que acomoda, apenas, duas espécies: Symbion pandora Funch e Kristensen, 1995 e S. americanus Obst, Funch e Kristensen, 2006. Este filo é caracterizado por um ciclo de vida assaz complexo, cuja posição filogenética tem sido debatida desde a sua descoberta. Esta dissertação visa aprofundar o conhecimento geral existente acerca destes enigmáticos e pouco explorados metazoários. Assim, vários aspectos da morfologia e ecologia de ciclióforos foram estudados através de observações in vivo, técnicas de microscopia e reconstrução tridimensional. A mioanatomia de várias fases do ciclo de vida é descrita para S. pandora e S. americanus. Os nossos resultados revelam uma similaridade contundente entre a musculatura das duas espécies. A mioanatomia geral de Symbion é, ainda, comparada à de outros metazoários. A expressão de algumas substâncias imunorreactivas, como são exemplo a serotonina e as sinapsinas, é investigada em várias formas do ciclo de vida. Quando comparados com outros representantes de Spiralia, conclui-se que a neuroanatomia geral dos ciclióforos se assemelha mais às formas larvares do que aos adultos. Apesar de possuírem um plano corporal sofisticado, com extensas áreas ciliadas e uma mioanatomia complexa, descobrimos que o macho de ambas as espécies Symbion é composto por apenas algumas dezenas de células. Baseando-nos nestas observações, inferimos que a complexidade dos metazoários não se relaciona com o tamanho corporal nem com o número de células de um organismo. Estudos sobre a ultra-estrutura da fêmea revelaram, entre outras estruturas, um putativo poro genital, extensões citoplasmáticas do oócito e glândulas posteriores. Morfologia e implicações funcionais destas estruturas são aqui discutidas. A anatomia do protonefrídeo da larva cordóide é descrita. A arquitectura deste órgão diverge daquela presente noutros representantes de Nephrozoa, particularmente ao nível da área de filtração da célula terminal. As nossas observações são discutidas em termos filogenéticos. A maturação sexual em ciclióforos é investigada. Os nossos resultados sugerem que a transição de reprodução assexual a sexual se relacione com a idade da forma séssil, a “feeding stage”. A presença da larva Prometeus assente no tronco desta também poderá influenciar o processo, embora mais estudos sejam desejáveis para o comprovar. Os nossos resultados são discutidos integrativa e comparativamente com o conhecimento prévio sobre Cycliophora. A cumulação deste conhecimento será essencial para a compreensão da evolução e filogenia deste enigmático filo.

Calibration de systèmes de caméras et projecteurs dans des applications de création multimédia

Ce mémoire s'intéresse à la vision par ordinateur appliquée à des projets d'art technologique. Le sujet traité est la calibration de systèmes de caméras et de projecteurs dans des applications de suivi et de reconstruction 3D en arts visuels et en art performatif. Le mémoire s'articule autour de deux collaborations avec les artistes québécois Daniel Danis et Nicolas Reeves. La géométrie projective et les méthodes de calibration classiques telles que la calibration planaire et la calibration par géométrie épipolaire sont présentées pour introduire les techniques utilisées dans ces deux projets. La collaboration avec Nicolas Reeves consiste à calibrer un système caméra-projecteur sur tête robotisée pour projeter des vidéos en temps réel sur des écrans cubiques mobiles. En plus d'appliquer des méthodes de calibration classiques, nous proposons une nouvelle technique de calibration de la pose d'une caméra sur tête robotisée. Cette technique utilise des plans elliptiques générés par l'observation d'un seul point dans le monde pour déterminer la pose de la caméra par rapport au centre de rotation de la tête robotisée. Le projet avec le metteur en scène Daniel Danis aborde les techniques de calibration de systèmes multi-caméras. Pour son projet de théâtre, nous avons développé un algorithme de calibration d'un réseau de caméras wiimotes. Cette technique basée sur la géométrie épipolaire permet de faire de la reconstruction 3D d'une trajectoire dans un grand volume à un coût minime. Les résultats des techniques de calibration développées sont présentés, de même que leur utilisation dans des contextes réels de performance devant public.