Some new research directions to explore in urban reconstruction

International audienceIn this paper we present an update on the geometric modeling of urban scenes from physical measurements. This field of research has been studied for more than thirty years, but remains an important challenge in many scientific communi-ties as photogrammetry, computer vision, robotics or computer graphics. After introducing the objectives and difficulties of urban reconstruction, we present an non-exhaustive overview of the approaches and trends that have inspired the research communities so far. We also propose some new research directions that might be worth investigating in the coming years

Proseduraalisen tietomallintamisen käyttöönotto kaupunkisuunnittelussa

This thesis examines procedural modeling as a tool for urban plan creation. Procedural modeling historically has been used for 3D visualization of natural features, but with the release of the soft-ware CityEngine in 2008 the technology can easily be adopted also in problem domains dealing with urban environments. The study begins with a requirement analysis conducted to explore the needs urban planning imposes on the technology, based on which a functional procedural modeling production system is built using the CityEngine platform and its Computer Generated Architecture (CGA) scripting language. A solution is presented to the problem of control in procedural generation methods by introducing the concept of a selectable “Level of Control” and how its implementation in the produced system enables the planner to flexibly assume the necessary amount of control over the generated model. The finished product is then compared against the presented requirements of accuracy, efficiency, ease of use, high visual qualities, and advanced analytical capabilities. The efficiency of the system measured as the ratio between user interactions (mouse clicks and keystrokes) and modeling output in the setting of the assessment is found out to be two to three times greater than the efficiency of a more established manual modeling software. The technology as demonstrated through the produced system is concluded to be especially suitable for preliminary land use studies estimating the building potentials of extensive land areas. Directions for future research with potential to expand the applicability of the technology are discussed.Tässä diplomityössä tutkitaan proseduraalista mallintamista kaupunkisuunnittelun työvälineenä. Proseduraalista mallintamista on historiallisesti käytetty luonnonmuotojen 3D-visualisoimiseen, mutta vuonna 2008 julkaistu CityEngine-ohjelma mahdollistaa teknologian helpon käyttöönoton myös rakennettua ympäristöä koskevissa aihepiireissä. Tutkielma alkaa analyysillä kaupunkisuunnittelun teknologiaan kohdistamista vaatimuksista, joiden perusteella rakennetaan CityEngineen ja sen Computer Generated Architecture (CGA) ohjel-mointikieleen perustuva proseduraalinen mallinnusjärjestelmä. Ratkaisuna proseduraaliseen mallintamiseen liittyvään kontrollin problematiikkaan esitellään käsite valittavasta ”kontrollitasosta”, ja kuinka sen implementaatio toteutetussa järjestelmässä mahdollistaa suunnittelijan ottaa joustavasti tarpeellisen määrän kontrollia generoitavan mallin suhteen. Valmista tuotetta verrataan esitettyihin tarkkuuden, tehokkuuden, käytön helppouden, korkealaatuisen visuaalisuuden, sekä kehittyneen analytiikan vaatimuksiin. Järjestelmän tehokkuus mitattuna käyttäjäinteraktioiden (hiiren klikkaukset ja näppäimistön painallukset) ja tuotetun mallin suhteena mittauksen asetelmassa on kahdesta kolmeen kertaa suurempi kuin vakiintuneemman manuaalisen mallinnusohjelman tehokkuus. Proseduraalisen mallintamisen, sellaisena kuin se tuotetussa järjestelmässä on implementoitu, todetaan olevan erityisen sopiva alustavien rakentamisen määrää laajoille alueille haarukoivien maankäyttötarkastelujen tuottamiseen. Työn lopuksi käsitellään teknologian käyttöaluetta laajentavia tutkimussuuntia

LOD Generation for Urban Scenes

International audienceWe introduce a novel approach that reconstructs 3D urban scenes in the form of levels of detail (LODs). Starting from raw data sets such as surface meshes generated by multi-view stereo systems, our algorithm proceeds in three main steps: classification, abstraction and reconstruction. From geometric attributes and a set of semantic rules combined with a Markov random field, we classify the scene into four meaningful classes. The abstraction step detects and regularizes planar structures on buildings, fits icons on trees, roofs and facades, and performs filtering and simplification for LOD generation. The abstracted data are then provided as input to the reconstruction step which generates watertight buildings through a min-cut formula-tion on a set of 3D arrangements. Our experiments on complex buildings and large scale urban scenes show that our approach generates meaningful LODs while being robust and scalable. By combining semantic segmentation and abstraction it also outperforms general mesh approximation ap-proaches at preserving urban structures

VISUAL SEMANTIC SEGMENTATION AND ITS APPLICATIONS

This dissertation addresses the difficulties of semantic segmentation when dealing with an extensive collection of images and 3D point clouds. Due to the ubiquity of digital cameras that help capture the world around us, as well as the advanced scanning techniques that are able to record 3D replicas of real cities, the sheer amount of visual data available presents many opportunities for both academic research and industrial applications. But the mere quantity of data also poses a tremendous challenge. In particular, the problem of distilling useful information from such a large repository of visual data has attracted ongoing interests in the fields of computer vision and data mining. Structural Semantics are fundamental to understanding both natural and man-made objects. Buildings, for example, are like languages in that they are made up of repeated structures or patterns that can be captured in images. In order to find these recurring patterns in images, I present an unsupervised frequent visual pattern mining approach that goes beyond co-location to identify spatially coherent visual patterns, regardless of their shape, size, locations and orientation. First, my approach categorizes visual items from scale-invariant image primitives with similar appearance using a suite of polynomial-time algorithms that have been designed to identify consistent structural associations among visual items, representing frequent visual patterns. After detecting repetitive image patterns, I use unsupervised and automatic segmentation of the identified patterns to generate more semantically meaningful representations. The underlying assumption is that pixels capturing the same portion of image patterns are visually consistent, while pixels that come from different backdrops are usually inconsistent. I further extend this approach to perform automatic segmentation of foreground objects from an Internet photo collection of landmark locations. New scanning technologies have successfully advanced the digital acquisition of large-scale urban landscapes. In addressing semantic segmentation and reconstruction of this data using LiDAR point clouds and geo-registered images of large-scale residential areas, I develop a complete system that simultaneously uses classification and segmentation methods to first identify different object categories and then apply category-specific reconstruction techniques to create visually pleasing and complete scene models

Model synthesis

Three-dimensional models are extensively used in nearly all types of computer graphics applications. The demand for 3D models is large and growing. However, despite extensive work in modeling for over four decades, model generation remains a labor-intensive and difficult process even with the best available tools. We present a new procedural modeling technique called model synthesis that is designed to generate many classes of objects. Model synthesis is inspired by developments in texture synthesis. Model synthesis is designed to automatically generate a large model that resembles a small example model provided by the user. Every small part of the generated model is identical to a small part of the example model. By altering the example model, a wide variety of objects can be produced. We present several different model synthesis algorithms and analyze their strengths and weaknesses. Discrete model synthesis generates models built out of small building blocks or model pieces. Continuous model synthesis generates models on set of parallel planes. We also show how to incorporate several additional user-defined constraints to control the large-scale structure of the model, to control how the objects are distributed, and to generate symmetric models. The generality of the approach will be demonstrated by showing many models produced using each approach including cities, landscapes, spaceships, and castles. The models contain hundreds of thousands of model pieces and are generated in only a few minutes

THE SOCIAL MEDIA IMAGE: MODES OF VISUAL ORDERING ON SOCIAL MEDIA

My dissertation considers the organization of large sets of user-generated photographs across social media platforms, and delineates the ways in which time and place are mediated through their presentation and analyses. Addressing the unprecedented scale of social media visual expressions, together with their implementation, structure and presentation within specific media platforms, I examine how visual social media data is processed, structured, and presented, and theorize the consequences of these forms for the ways we culturally understand and experience contemporary visual information. Taking an integrated approach, this work offers a qualitative and quantitative analysis, and draws on methodologies from media theory, information science, software studies, art history, cultural studies, and computer science. I combine distant critical reading of larger organizational patterns and their cultural meanings (studying visual arrangement in exiting platforms, experimental computational research, and artistic works) with a close analytical reading of groups of photos, using computational and visualization tools. This twin process allows me to develop my theoretical understanding based on particular results, but also illustrates the problem that is the focus of this dissertation: how to understand new visual production scales, their organizations, and their interpretation

Modeling the appearance and behavior of urban spaces

The complexity of urban spaces and of the phenomena that take place in them calls for the use of customized computational tools within the city planning and design workflow. We develop a framework that benefits different parts of this workflow, including the design of 3D representations of planned developments, the estimated prediction of the effects of these developments on city behavior, and the visualization of these effects for further analysis. Our approach infers values of urban model variables from user-specified geometric and behavioral constraints and high-level design goals, enforces the procedural generation process to produce geometric assets that behaviorally and geometrically resemble plausible real-world cities, and automatically creates 3D urban models for visualizing behavioral phenomena occurring in urban spaces. Our framework allows users to experiment with alternative spatial and functional configurations of a city, while interactively receiving visual and quantitative feedback that facilitates assessing and understanding the effects of their choices