Artificial Neural Networks as Decision-Makers for Stereo Matching

This paper investigates the use of artificial neural networks to help making a decision on matching of stereo images. An image matching technique based on extracting features from segmented regions is adopted in this work, and a neural network framework is applied for region matching of stereo photographs. Two types of neural networks are used, the radial basis network, (RB) for learning clustering, and the back propagation (BP) network for learning image matching. The (RB) neural network is to cluster the regions according to the locations of their centered points. For each region, the BP network uses differential features as input training data. While training and testing the system, multiple features are extracted and used for enhancing the accuracy of the matching process. Features include (compactness, Euler number, and invariant moments) for each region. Results obtained from the neural networks (namely; clustering and initial matching array) are used to select the best matching pair. Results are showing a good matching accuracy

Semi-automatic 3D reconstruction of urban areas using epipolar geometry and template matching

WOS:000240143800002 (Nº de Acesso Web of Science)In this work we describe a novel technique for semi-automatic three-dimensional (3D) reconstruction of urban areas, from airborne stereo-pair images whose output is VRML or DXF. The main challenge is to compute the relevant information—building's height and volume, roof's description, and texture—algorithmically, because it is very time consuming and thus expensive to produce it manually for large urban areas. The algorithm requires some initial calibration input and is able to compute the above-mentioned building characteristics from the stereo pair and the availability of the 2D CAD and the digital elevation model of the same area, with no knowledge of the camera pose or its intrinsic parameters. To achieve this, we have used epipolar geometry, homography computation, automatic feature extraction and we have solved the feature correspondence problem in the stereo pair, by using template matching

Advances in Stereo Vision

Stereopsis is a vision process whose geometrical foundation has been known for a long time, ever since the experiments by Wheatstone, in the 19th century. Nevertheless, its inner workings in biological organisms, as well as its emulation by computer systems, have proven elusive, and stereo vision remains a very active and challenging area of research nowadays. In this volume we have attempted to present a limited but relevant sample of the work being carried out in stereo vision, covering significant aspects both from the applied and from the theoretical standpoints

SfM for Orthophoto Generation: A Winning Approach for Cultural Heritage Knowledge

3D detailed models derived from digital survey techniques have increasingly developed and focused in many field of application. The high detailed content and accuracy of such models make them so attractive and usable for large sets of purposes in Cultural Heritage. The present paper focuses on one of the main techniques used nowadays for Cultural Heritage survey and documentation: the image matching approach or Structure from Motion (SfM) technique. According to the low cost nature and the rich content of derivable information, these techniques are extremely strategic in poor available resources sectors such as Cultural Heritage documentation. <br><br> After an overview of the employed algorithms and used approaches of SfM computer vision based techniques, the paper is focused in a critical analysis of the strategy used by two common employed software: the commercial suite Agisoft Photoscan and the open source tool MicMac realized by IGN France. The experimental section is focused on the description of applied tests (from RPAS data to terrestrial acquisitions), purposed to compare different solutions in various featured study cases. Finally, the accuracy assessment of the achieved products is compared and analyzed according to the strategy employed by the studied software

Digital photogrammetry for visualisation in architecture and archaeology

Bibliography: leaves 117-125.The task of recording our physical heritage is of significant importance: our past cannot be divorced from the present and it plays an integral part in the shaping of our future. This applies not only to structures that are hundreds of years old, but relatively more recent architectural structures also require adequate documentation if they are to be preserved for future generations. In recording such structures, the traditional 2D methods are proving inadequate. It will be beneficial to conservationists, archaeologists, researchers, historians and students alike if accurate and extensive digital 3D models of archaeological structures can be generated. This thesis investigates a method of creating such models, using digital photogrammetry. Three different types of model were generated: 1. the simple CAD (Computer Aided Design) model; 2. an amalgamation of 3D line drawings; and 3. an accurate surface model of the building using DSMs (Digital Surface Models) and orthophotos

Individual tree measurements by means of digital aerial photogrammetry

Korpela, I. 2004. Individual tree measurements by means of digital aerial photogrammetry. Silva Fennica Monographs 3. 93 p. This study explores the plausibility of the use of multi-scale, CIR aerial photographs to conduct forest inventory at the individual tree level. Multiple digitised aerial photographs are used for manual and semi-automatic 3D positioning of tree tops, for species classification, and for measurements on tree height and crown width. A new tree top positioning algorithm is presented and tested. It incorporates template matching in a 3D search space. Also, a new method is presented for tree species classification. In it, a partition of the image space according to the continuously varying image-object-sun geometry of aerial views is performed. Discernibility of trees in aerial images is studied. The measurement accuracy and overall measurability of crown width by using manual image measurements is investigated. A simulation study is used to examine the combined effects of discernibility and photogrammetric measurement errors on stand variables. The study material contained large-scale colour and CIR image material and 7708 trees from 24 fully mappe

Object-Based Greenhouse Classification from GeoEye-1 and WorldView-2 Stereo Imagery

Remote sensing technologies have been commonly used to perform greenhouse detection and mapping. In this research, stereo pairs acquired by very high-resolution optical satellites GeoEye-1 (GE1) and WorldView-2 (WV2) have been utilized to carry out the land cover classification of an agricultural area through an object-based image analysis approach, paying special attention to greenhouses extraction. The main novelty of this work lies in the joint use of single-source stereo-photogrammetrically derived heights and multispectral information from both panchromatic and pan-sharpened orthoimages. The main features tested in this research can be grouped into different categories, such as basic spectral information, elevation data (normalized digital surface model; nDSM), band indexes and ratios, texture and shape geometry. Furthermore, spectral information was based on both single orthoimages and multiangle orthoimages. The overall accuracy attained by applying nearest neighbor and support vector machine classifiers to the four multispectral bands of GE1 were very similar to those computed from WV2, for either four or eight multispectral bands. Height data, in the form of nDSM, were the most important feature for greenhouse classification. The best overall accuracy values were close to 90%, and they were not improved by using multiangle orthoimages

Algorithms for the reconstruction, analysis, repairing and enhancement of 3D urban models from multiple data sources

Over the last few years, there has been a notorious growth in the field of digitization of 3D buildings and urban environments. The substantial improvement of both scanning hardware and reconstruction algorithms has led to the development of representations of buildings and cities that can be remotely transmitted and inspected in real-time. Among the applications that implement these technologies are several GPS navigators and virtual globes such as Google Earth or the tools provided by the Institut Cartogràfic i Geològic de Catalunya. In particular, in this thesis, we conceptualize cities as a collection of individual buildings. Hence, we focus on the individual processing of one structure at a time, rather than on the larger-scale processing of urban environments. Nowadays, there is a wide diversity of digitization technologies, and the choice of the appropriate one is key for each particular application. Roughly, these techniques can be grouped around three main families: - Time-of-flight (terrestrial and aerial LiDAR). - Photogrammetry (street-level, satellite, and aerial imagery). - Human-edited vector data (cadastre and other map sources). Each of these has its advantages in terms of covered area, data quality, economic cost, and processing effort. Plane and car-mounted LiDAR devices are optimal for sweeping huge areas, but acquiring and calibrating such devices is not a trivial task. Moreover, the capturing process is done by scan lines, which need to be registered using GPS and inertial data. As an alternative, terrestrial LiDAR devices are more accessible but cover smaller areas, and their sampling strategy usually produces massive point clouds with over-represented plain regions. A more inexpensive option is street-level imagery. A dense set of images captured with a commodity camera can be fed to state-of-the-art multi-view stereo algorithms to produce realistic-enough reconstructions. One other advantage of this approach is capturing high-quality color data, whereas the geometric information is usually lacking. In this thesis, we analyze in-depth some of the shortcomings of these data-acquisition methods and propose new ways to overcome them. Mainly, we focus on the technologies that allow high-quality digitization of individual buildings. These are terrestrial LiDAR for geometric information and street-level imagery for color information. Our main goal is the processing and completion of detailed 3D urban representations. For this, we will work with multiple data sources and combine them when possible to produce models that can be inspected in real-time. Our research has focused on the following contributions: - Effective and feature-preserving simplification of massive point clouds. - Developing normal estimation algorithms explicitly designed for LiDAR data. - Low-stretch panoramic representation for point clouds. - Semantic analysis of street-level imagery for improved multi-view stereo reconstruction. - Color improvement through heuristic techniques and the registration of LiDAR and imagery data. - Efficient and faithful visualization of massive point clouds using image-based techniques.Durant els darrers anys, hi ha hagut un creixement notori en el camp de la digitalització d'edificis en 3D i entorns urbans. La millora substancial tant del maquinari d'escaneig com dels algorismes de reconstrucció ha portat al desenvolupament de representacions d'edificis i ciutats que es poden transmetre i inspeccionar remotament en temps real. Entre les aplicacions que implementen aquestes tecnologies hi ha diversos navegadors GPS i globus virtuals com Google Earth o les eines proporcionades per l'Institut Cartogràfic i Geològic de Catalunya. En particular, en aquesta tesi, conceptualitzem les ciutats com una col·lecció d'edificis individuals. Per tant, ens centrem en el processament individual d'una estructura a la vegada, en lloc del processament a gran escala d'entorns urbans. Avui en dia, hi ha una àmplia diversitat de tecnologies de digitalització i la selecció de l'adequada és clau per a cada aplicació particular. Aproximadament, aquestes tècniques es poden agrupar en tres famílies principals: - Temps de vol (LiDAR terrestre i aeri). - Fotogrametria (imatges a escala de carrer, de satèl·lit i aèries). - Dades vectorials editades per humans (cadastre i altres fonts de mapes). Cadascun d'ells presenta els seus avantatges en termes d'àrea coberta, qualitat de les dades, cost econòmic i esforç de processament. Els dispositius LiDAR muntats en avió i en cotxe són òptims per escombrar àrees enormes, però adquirir i calibrar aquests dispositius no és una tasca trivial. A més, el procés de captura es realitza mitjançant línies d'escaneig, que cal registrar mitjançant GPS i dades inercials. Com a alternativa, els dispositius terrestres de LiDAR són més accessibles, però cobreixen àrees més petites, i la seva estratègia de mostreig sol produir núvols de punts massius amb regions planes sobrerepresentades. Una opció més barata són les imatges a escala de carrer. Es pot fer servir un conjunt dens d'imatges capturades amb una càmera de qualitat mitjana per obtenir reconstruccions prou realistes mitjançant algorismes estèreo d'última generació per produir. Un altre avantatge d'aquest mètode és la captura de dades de color d'alta qualitat. Tanmateix, la informació geomètrica resultant sol ser de baixa qualitat. En aquesta tesi, analitzem en profunditat algunes de les mancances d'aquests mètodes d'adquisició de dades i proposem noves maneres de superar-les. Principalment, ens centrem en les tecnologies que permeten una digitalització d'alta qualitat d'edificis individuals. Es tracta de LiDAR terrestre per obtenir informació geomètrica i imatges a escala de carrer per obtenir informació sobre colors. El nostre objectiu principal és el processament i la millora de representacions urbanes 3D amb molt detall. Per a això, treballarem amb diverses fonts de dades i les combinarem quan sigui possible per produir models que es puguin inspeccionar en temps real. La nostra investigació s'ha centrat en les següents contribucions: - Simplificació eficaç de núvols de punts massius, preservant detalls d'alta resolució. - Desenvolupament d'algoritmes d'estimació normal dissenyats explícitament per a dades LiDAR. - Representació panoràmica de baixa distorsió per a núvols de punts. - Anàlisi semàntica d'imatges a escala de carrer per millorar la reconstrucció estèreo de façanes. - Millora del color mitjançant tècniques heurístiques i el registre de dades LiDAR i imatge. - Visualització eficient i fidel de núvols de punts massius mitjançant tècniques basades en imatges