Pre-processing, classification and semantic querying of large-scale Earth observation spaceborne/airborne/terrestrial image databases: Process and product innovations.

By definition of Wikipedia, “big data is the term adopted for a collection of data sets so large and complex that it becomes difficult to process using on-hand database management tools or traditional data processing applications. The big data challenges typically include capture, curation, storage, search, sharing, transfer, analysis and visualization”. Proposed by the intergovernmental Group on Earth Observations (GEO), the visionary goal of the Global Earth Observation System of Systems (GEOSS) implementation plan for years 2005-2015 is systematic transformation of multisource Earth Observation (EO) “big data” into timely, comprehensive and operational EO value-adding products and services, submitted to the GEO Quality Assurance Framework for Earth Observation (QA4EO) calibration/validation (Cal/Val) requirements. To date the GEOSS mission cannot be considered fulfilled by the remote sensing (RS) community. This is tantamount to saying that past and existing EO image understanding systems (EO-IUSs) have been outpaced by the rate of collection of EO sensory big data, whose quality and quantity are ever-increasing. This true-fact is supported by several observations. For example, no European Space Agency (ESA) EO Level 2 product has ever been systematically generated at the ground segment. By definition, an ESA EO Level 2 product comprises a single-date multi-spectral (MS) image radiometrically calibrated into surface reflectance (SURF) values corrected for geometric, atmospheric, adjacency and topographic effects, stacked with its data-derived scene classification map (SCM), whose thematic legend is general-purpose, user- and application-independent and includes quality layers, such as cloud and cloud-shadow. Since no GEOSS exists to date, present EO content-based image retrieval (CBIR) systems lack EO image understanding capabilities. Hence, no semantic CBIR (SCBIR) system exists to date either, where semantic querying is synonym of semantics-enabled knowledge/information discovery in multi-source big image databases. In set theory, if set A is a strict superset of (or strictly includes) set B, then A B. This doctoral project moved from the working hypothesis that SCBIR computer vision (CV), where vision is synonym of scene-from-image reconstruction and understanding EO image understanding (EO-IU) in operating mode, synonym of GEOSS ESA EO Level 2 product human vision. Meaning that necessary not sufficient pre-condition for SCBIR is CV in operating mode, this working hypothesis has two corollaries. First, human visual perception, encompassing well-known visual illusions such as Mach bands illusion, acts as lower bound of CV within the multi-disciplinary domain of cognitive science, i.e., CV is conditioned to include a computational model of human vision. Second, a necessary not sufficient pre-condition for a yet-unfulfilled GEOSS development is systematic generation at the ground segment of ESA EO Level 2 product. Starting from this working hypothesis the overarching goal of this doctoral project was to contribute in research and technical development (R&D) toward filling an analytic and pragmatic information gap from EO big sensory data to EO value-adding information products and services. This R&D objective was conceived to be twofold. First, to develop an original EO-IUS in operating mode, synonym of GEOSS, capable of systematic ESA EO Level 2 product generation from multi-source EO imagery. EO imaging sources vary in terms of: (i) platform, either spaceborne, airborne or terrestrial, (ii) imaging sensor, either: (a) optical, encompassing radiometrically calibrated or uncalibrated images, panchromatic or color images, either true- or false color red-green-blue (RGB), multi-spectral (MS), super-spectral (SS) or hyper-spectral (HS) images, featuring spatial resolution from low (> 1km) to very high (< 1m), or (b) synthetic aperture radar (SAR), specifically, bi-temporal RGB SAR imagery. The second R&D objective was to design and develop a prototypical implementation of an integrated closed-loop EO-IU for semantic querying (EO-IU4SQ) system as a GEOSS proof-of-concept in support of SCBIR. The proposed closed-loop EO-IU4SQ system prototype consists of two subsystems for incremental learning. A primary (dominant, necessary not sufficient) hybrid (combined deductive/top-down/physical model-based and inductive/bottom-up/statistical model-based) feedback EO-IU subsystem in operating mode requires no human-machine interaction to automatically transform in linear time a single-date MS image into an ESA EO Level 2 product as initial condition. A secondary (dependent) hybrid feedback EO Semantic Querying (EO-SQ) subsystem is provided with a graphic user interface (GUI) to streamline human-machine interaction in support of spatiotemporal EO big data analytics and SCBIR operations. EO information products generated as output by the closed-loop EO-IU4SQ system monotonically increase their value-added with closed-loop iterations

Texture analysis using the trace transform

EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Inpainting de modèles 3D pour la réalité diminuée : "couper/coller" réaliste pour l'aménagement d'intérieur

Par opposition à la Réalité Augmentée qui consiste à ajouter des éléments virtuels à un environnement réel, la Réalité Diminuée consiste à supprimer des éléments réels d'un environnement. Le but est d'effectuer un rendu visuel d'une scène 3D où les éléments "effacés" ne sont plus présents : la difficulté consiste à créer une image de sorte que la diminution ne soit pas perceptible par l'utilisateur. Il faut donc venir compléter la scène initialement cachée par ces éléments, en effectuant une opération d'inpainting qui prenne en compte la géométrie de la pièce, sa texture (structurée ou non), et la luminosité ambiante de l'environnement. Par exemple, l’œil humain est sensible à la régularité d'une texture. L'un des objectifs d'Innersense, entreprise spécialisée dans l'aménagement virtuel d’intérieurs, est de développer un produit capable d'enlever des éléments présents dans une pièce d'intérieur. Une fois la suppression virtuelle des meubles existants effectuée , il sera alors possible d'ajouter des meubles virtuels dans l'espace laissé vacant. L'objectif de cette thèse CIFRE est donc de mettre en place un scénario de réalité diminuée pouvant être exécuté sur un système mobile (tablette IOS ou Android) qui génère des images photo-réalistes de la scène diminuée. Pour cela, à partir d’un modèle géométrique de la pièce d'intérieur que l'on veut altérer, nous adaptons et améliorons des procédures d'effacement d'éléments d'une image appelées inpainting dans une image 2D. Ensuite, nous appliquons ces techniques dans le contexte 3D intérieur pour tenir compte de la géométrie de la scène. Enfin, nous analysons la luminosité pour augmenter le réalisme des zones complétées.Dans cette thèse, nous rappelons d'abord les différents travaux académiques et les solutions industrielles existantes. Nous évoquons leurs avantages et leurs limites. Nous abordons ensuite les différentes techniques d'inpainting existantes pour introduire notre première contribution qui propose d'adapter une des méthodes de l’état de l’art pour prendre en compte de la structure du motif de la texture. La problématique de la luminosité est ensuite abordée en proposant un processus qui traite séparément la texture et la variation de la luminosité. Nous présentons ensuite une troisième contribution qui propose un critère de confiance basé sur des considérations radiométriques pour sélectionner une information selon sa qualité dans le processus d'inpainting. Nous proposons une dernière contribution basée sur la complétion de texture de modèles 3D non planaires reconstruits à partir de peu d’images et donc présentant une texture incomplète. Enfin, nous montrons les applications développées grâce à ces travaux dans le contexte des scènes d'intérieur considérées par Innersens

Linking structure and functioning of hydrological systems - How to achieve necessary experimental and model complexity with adequate effort

This thesis quests after minimum adequacy of model complexity, geophysical exploration and functional unit identification through examples from the Attert experimental basin. With emphasis on a joined examination of theoretical concepts, experimental methodology and modelling approaches the study addresses landscape and process analysis, targeted experiments at the plot- and hillslope-scale and the development of a novel Lagrangian model framework for diffusive and advective soil water dynamics

Photogrammetric suite to manage the survey workflow in challenging environments and conditions

The present work is intended in providing new and innovative instruments to support the photogrammetric survey workflow during all its phases. A suite of tools has been conceived in order to manage the planning, the acquisition, the post-processing and the restitution steps, with particular attention to the rigorousness of the approach and to the final precision. The main focus of the research has been the implementation of the tool MAGO, standing for Adaptive Mesh for Orthophoto Generation. Its novelty consists in the possibility to automatically reconstruct \u201cunrolled\u201d orthophotos of adjacent fa\ue7ades of a building using the point cloud, instead of the mesh, as input source for the orthophoto reconstruction. The second tool has been conceived as a photogrammetric procedure based on Bundle Block Adjustment. The same issue is analysed from two mirrored perspectives: on the one hand, the use of moving cameras in a static scenario in order to manage real-time indoor navigation; on the other hand, the use of static cameras in a moving scenario in order to achieve the simultaneously reconstruction of the 3D model of the changing object. A third tool named U.Ph.O., standing for Unmanned Photogrammetric Office, has been integrated with a new module. The general aim is on the one hand to plan the photogrammetric survey considering the expected precision, computed on the basis of a network simulation, and on the other hand to check if the achieved survey has been collected compatibly with the planned conditions. The provided integration concerns the treatment of surfaces with a generic orientation further than the ones with a planimetric development. After a brief introduction, a general description about the photogrammetric principles is given in the first chapter of the dissertation; a chapter follows about the parallelism between Photogrammetry and Computer Vision and the contribution of this last in the development of the described tools. The third chapter specifically regards, indeed, the implemented software and tools, while the fourth contains the training test and the validation. Finally, conclusions and future perspectives are reported

Symmetry in Quantum Theory of Gravity

This edited collection explores current approaches to understanding space, time, and gravity within a quantum-theoretical framework. In most such approaches, the three-dimensional space of ordinary perception and action is physically fundamental, but is rather emergent from underlying structures or dynamics that can, in general, be described in terms of information flows. Processes such as measurement and computation are, therefore, fundamental to the notion of physical space

Introduction: Ways of Machine Seeing

How do machines, and, in particular, computational technologies, change the way we see the world? This special issue brings together researchers from a wide range of disciplines to explore the entanglement of machines and their ways of seeing from new critical perspectives. This 'editorial' is for a special issue of AI & Society, which includes contributions from: María Jesús Schultz Abarca, Peter Bell, Tobias Blanke, Benjamin Bratton, Claudio Celis Bueno, Kate Crawford, Iain Emsley, Abelardo Gil-Fournier, Daniel Chávez Heras, Vladan Joler, Nicolas Malevé, Lev Manovich, Nicholas Mirzoeff, Perle Møhl, Bruno Moreschi, Fabian Offert, Trevor Paglan, Jussi Parikka, Luciana Parisi, Matteo Pasquinelli, Gabriel Pereira, Carloalberto Treccani, Rebecca Uliasz, and Manuel van der Veen

Models, Simulations, and the Reduction of Complexity

Modern science is a model-building activity. But how are models contructed? How are they related to theories and data? How do they explain complex scientific phenomena, and which role do computer simulations play? To address these questions which are highly relevant to scientists as well as to philosophers of science, 8 leading natural, engineering and social scientists reflect upon their modeling work, and 8 philosophers provide a commentary