1,729 research outputs found
Automatic segmentation and reconstruction of traffic accident scenarios from mobile laser scanning data
Virtual reconstruction of historic sites, planning of restorations and attachments of new building parts, as well as forest inventory are few examples of fields that benefit from the application of 3D surveying data. Originally using 2D photo based documentation and manual distance measurements, the 3D information obtained from multi camera and laser scanning systems realizes a noticeable improvement regarding the surveying times and the amount of generated 3D information. The 3D data allows a detailed post processing and better visualization of all relevant spatial information. Yet, for the extraction of the required information from the raw scan data and for the generation of useable visual output, time-consuming, complex user-based data processing is still required, using the commercially available 3D software tools.
In this context, the automatic object recognition from 3D point cloud and depth data has been discussed in many different works. The developed tools and methods however, usually only focus on a certain kind of object or the detection of learned invariant surface shapes. Although the resulting methods are applicable for certain practices of data segmentation, they are not necessarily suitable for arbitrary tasks due to the varying requirements of the different fields of research.
This thesis presents a more widespread solution for automatic scene reconstruction from 3D point clouds, targeting street scenarios, specifically for the task of traffic accident scene analysis and documentation. The data, obtained by sampling the scene using a mobile scanning system is evaluated, segmented, and finally used to generate detailed 3D information of the scanned environment.
To realize this aim, this work adapts and validates various existing approaches on laser scan segmentation regarding the application on accident relevant scene information, including road surfaces and markings, vehicles, walls, trees and other salient objects. The approaches are therefore evaluated regarding their suitability and limitations for the given tasks, as well as for possibilities concerning the combined application together with other procedures. The obtained knowledge is used for the development of new algorithms and procedures to allow a satisfying segmentation and reconstruction of the scene, corresponding to the available sampling densities and precisions.
Besides the segmentation of the point cloud data, this thesis presents different visualization and reconstruction methods to achieve a wider range of possible applications of the developed system for data export and utilization in different third party software tools
3D photogrammetric data modeling and optimization for multipurpose analysis and representation of Cultural Heritage assets
This research deals with the issues concerning the processing, managing, representation
for further dissemination of the big amount of 3D data today achievable and storable with
the modern geomatic techniques of 3D metric survey. In particular, this thesis is focused
on the optimization process applied to 3D photogrammetric data of Cultural Heritage
assets.
Modern Geomatic techniques enable the acquisition and storage of a big amount of data,
with high metric and radiometric accuracy and precision, also in the very close range
field, and to process very detailed 3D textured models. Nowadays, the photogrammetric
pipeline has well-established potentialities and it is considered one of the principal
technique to produce, at low cost, detailed 3D textured models.
The potentialities offered by high resolution and textured 3D models is today well-known
and such representations are a powerful tool for many multidisciplinary purposes, at
different scales and resolutions, from documentation, conservation and restoration to
visualization and education. For example, their sub-millimetric precision makes them
suitable for scientific studies applied to the geometry and materials (i.e. for structural and
static tests, for planning restoration activities or for historical sources); their high fidelity
to the real object and their navigability makes them optimal for web-based visualization
and dissemination applications. Thanks to the improvement made in new visualization
standard, they can be easily used as visualization interface linking different kinds of
information in a highly intuitive way. Furthermore, many museums look today for more
interactive exhibitions that may increase the visitors’ emotions and many recent
applications make use of 3D contents (i.e. in virtual or augmented reality applications and
through virtual museums).
What all of these applications have to deal with concerns the issue deriving from the
difficult of managing the big amount of data that have to be represented and navigated.
Indeed, reality based models have very heavy file sizes (also tens of GB) that makes them
difficult to be handled by common and portable devices, published on the internet or
managed in real time applications. Even though recent advances produce more and more
sophisticated and capable hardware and internet standards, empowering the ability to
easily handle, visualize and share such contents, other researches aim at define a common
pipeline for the generation and optimization of 3D models with a reduced number of
polygons, however able to satisfy detailed radiometric and geometric requests.
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This thesis is inserted in this scenario and focuses on the 3D modeling process of
photogrammetric data aimed at their easy sharing and visualization. In particular, this
research tested a 3D models optimization, a process which aims at the generation of Low
Polygons models, with very low byte file size, processed starting from the data of High
Poly ones, that nevertheless offer a level of detail comparable to the original models. To
do this, several tools borrowed from the game industry and game engine have been used.
For this test, three case studies have been chosen, a modern sculpture of a contemporary
Italian artist, a roman marble statue, preserved in the Civic Archaeological Museum of
Torino, and the frieze of the Augustus arch preserved in the city of Susa (Piedmont-
Italy). All the test cases have been surveyed by means of a close range photogrammetric
acquisition and three high detailed 3D models have been generated by means of a
Structure from Motion and image matching pipeline. On the final High Poly models
generated, different optimization and decimation tools have been tested with the final aim
to evaluate the quality of the information that can be extracted by the final optimized
models, in comparison to those of the original High Polygon one. This study showed how
tools borrowed from the Computer Graphic offer great potentialities also in the Cultural
Heritage field. This application, in fact, may meet the needs of multipurpose and
multiscale studies, using different levels of optimization, and this procedure could be
applied to different kind of objects, with a variety of different sizes and shapes, also on
multiscale and multisensor data, such as buildings, architectural complexes, data from
UAV surveys and so on
On the popularization of digital close-range photogrammetry: a handbook for new users.
Εθνικό Μετσόβιο Πολυτεχνείο--Μεταπτυχιακή Εργασία. Διεπιστημονικό-Διατμηματικό Πρόγραμμα Μεταπτυχιακών Σπουδών (Δ.Π.Μ.Σ.) “Γεωπληροφορική
Multi-LiDAR Mapping for Scene Segmentation in Indoor Environments for Mobile Robots
Nowadays, most mobile robot applications use two-dimensional LiDAR for indoor mapping,
navigation, and low-level scene segmentation. However, single data type maps are not enough
in a six degree of freedom world. Multi-LiDAR sensor fusion increments the capability of robots to
map on different levels the surrounding environment. It exploits the benefits of several data types,
counteracting the cons of each of the sensors. This research introduces several techniques to achieve
mapping and navigation through indoor environments. First, a scan matching algorithm based on
ICP with distance threshold association counter is used as a multi-objective-like fitness function.
Then, with Harmony Search, results are optimized without any previous initial guess or odometry. A
global map is then built during SLAM, reducing the accumulated error and demonstrating better
results than solo odometry LiDAR matching. As a novelty, both algorithms are implemented in
2D and 3D mapping, overlapping the resulting maps to fuse geometrical information at different
heights. Finally, a room segmentation procedure is proposed by analyzing this information, avoiding
occlusions that appear in 2D maps, and proving the benefits by implementing a door recognition
system. Experiments are conducted in both simulated and real scenarios, proving the performance of
the proposed algorithms.This work was supported by the funding from HEROITEA: Heterogeneous Intelligent
Multi-Robot Team for Assistance of Elderly People (RTI2018-095599-B-C21), funded by Spanish Ministerio
de Economia y Competitividad, RoboCity2030-DIH-CM, Madrid Robotics Digital Innovation
Hub, S2018/NMT-4331, funded by “Programas de Actividades I+D en la Comunidad de Madrid”
and cofunded by Structural Funds of the EU.
We acknowledge the R&D&I project PLEC2021-007819 funded by MCIN/AEI/
10.13039/501100011033 and by the European Union NextGenerationEU/PRTR and the Comunidad de
Madrid (Spain) under the multiannual agreement with Universidad Carlos III de Madrid (“Excelencia
para el Profesorado Universitario’—EPUC3M18) part of the fifth regional research plan 2016–2020
Configurable nD-visualization for complex Building Information Models
With the ongoing development of building information modelling (BIM) towards a comprehensive coverage of all construction project information in a semantically explicit way, visual representations became decoupled from the building information models. While traditional construction drawings implicitly contained the visual representation besides the information, nowadays they are generated on the fly, hard-coded in software applications dedicated to other tasks such as analysis, simulation, structural design or communication.
Due to the abstract nature of information models and the increasing amount of digital information captured during construction projects, visual representations are essential for humans in order to access the information, to understand it, and to engage with it. At the same time digital media open up the new field of interactive visualizations.
The full potential of BIM can only be unlocked with customized task-specific visualizations, with engineers and architects actively involved in the design and development process of these visualizations. The visualizations must be reusable and reliably reproducible during communication processes. Further, to support creative problem solving, it must be possible to modify and refine them. This thesis aims at reconnecting building information models and their visual representations: on a theoretic level, on the level of methods and in terms of tool support.
First, the research seeks to improve the knowledge about visualization generation in conjunction with current BIM developments such as the multimodel. The approach is based on the reference model of the visualization pipeline and addresses structural as well as quantitative aspects of the visualization generation. Second, based on the theoretic foundation, a method is derived to construct visual representations from given visualization specifications. To this end, the idea of a domain-specific language (DSL) is employed. Finally, a software prototype proofs the concept. Using the visualization framework, visual representations can be generated from a specific building information model and a specific visualization description.Mit der fortschreitenden Entwicklung des Building Information Modelling (BIM) hin zu einer umfassenden Erfassung aller Bauprojektinformationen in einer semantisch expliziten Weise werden Visualisierungen von den Gebäudeinformationen entkoppelt. Während traditionelle Architektur- und Bauzeichnungen die visuellen Reprä̈sentationen implizit als Träger der Informationen enthalten, werden sie heute on-the-fly generiert.
Die Details ihrer Generierung sind festgeschrieben in Softwareanwendungen, welche eigentlich für andere Aufgaben wie Analyse, Simulation, Entwurf oder Kommunikation ausgelegt sind. Angesichts der abstrakten Natur von Informationsmodellen und der steigenden Menge digitaler Informationen, die im Verlauf von Bauprojekten erfasst werden, sind visuelle Repräsentationen essentiell, um sich die Information erschließen, sie verstehen, durchdringen und mit ihnen arbeiten zu können. Gleichzeitig entwickelt sich durch die digitalen Medien eine neues Feld der interaktiven Visualisierungen.
Das volle Potential von BIM kann nur mit angepassten aufgabenspezifischen Visualisierungen erschlossen werden, bei denen Ingenieur*innen und Architekt*innen aktiv in den Entwurf und die Entwicklung dieser Visualisierungen einbezogen werden. Die Visualisierungen müssen wiederverwendbar sein und in Kommunikationsprozessen zuverlässig reproduziert werden können. Außerdem muss es möglich sein, Visualisierungen zu modifizieren und neu zu definieren, um das kreative Problemlösen zu unterstützen.
Die vorliegende Arbeit zielt darauf ab, Gebäudemodelle und ihre visuellen Repräsentationen wieder zu verbinden: auf der theoretischen Ebene, auf der Ebene der Methoden und hinsichtlich der unterstützenden Werkzeuge. Auf der theoretischen Ebene trägt die Arbeit zunächst dazu bei, das Wissen um die Erstellung von Visualisierungen im Kontext von Bauprojekten zu erweitern. Der verfolgte Ansatz basiert auf dem Referenzmodell der Visualisierungspipeline und geht dabei sowohl auf strukturelle als auch auf quantitative Aspekte des Visualisierungsprozesses ein. Zweitens wird eine Methode entwickelt, die visuelle Repräsentationen auf Basis gegebener Visualisierungsspezifikationen generieren kann. Schließlich belegt ein Softwareprototyp die Realisierbarkeit des Konzepts. Mit dem entwickelten Framework können visuelle Repräsentationen aus jeweils einem spezifischen Gebäudemodell und einer spezifischen Visualisierungsbeschreibung generiert werden
Action intention recognition for proactive human assistance in domestic environments
The current Master’s Thesis in Automatics, Control and Robotics covers the development and implementation of an Action Intention Recognition algorithm for proactive human assistance in domestic environments. The proposed solution is based on the use of data provided by a real time RGBD Object Recognition process which captures object state changes inside a defined region of interest of the domestic environment setup. A background analysis is performed to analyze state of the art approaches to both real time RGBD object recognition and action intention recognition methods. The preliminary analysis serves as the base for the proposal of a new volume descriptor for object categorization and an improved formalism for Activation Spreading Networks in the context of action intention recognition. Several tests are performed to study the performance of the proposed solution and its results are analyzed to define the conclusions of the project and propose future work. Finally, the project budget and environmental impact as well as the project schedule are presented and briefly discusse
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