When we consider the nature of the scientific community in conjunction with a sense of typical economic circumstances we find that there are two distinct paths for development. One path involves hypothesis testing and evolution of strategies that are linked with iterations in equipment advances. A second, more complicated scenario, can involve external influences whether economic, political, or otherwise, such as the government closure of NASA's space program in 2011 which will no doubt influence research in associated fields. The following chapters are an account of examples of two statistical techniques and the importance of both on the two relatively unrelated geological fields of coastal geomorphology and ground water hydrology. The first technique applies a multi-dimensional approach to defining groundwater water table response based on precipitation in areas where it can reasonably be assumed to be the only recharge. The second technique applies a high resolution multi-scalar approach to a geologic setting most often restricted to either high resolution locally, or low resolution regionally. This technique uses time-frequency analysis to characterize cuspate patterns in LIDAR data are introduced using examples from the Atlantic coast of Florida, United States. These techniques permit the efficient study of beachface landforms over many kilometers of coastline at multiple spatial scales. From a LIDAR image, a beach-parallel spatial series is generated. Here, this series is the shore-normal position of a specific elevation (contour line). Well-established time-frequency analysis techniques, wavelet transforms, and S-Transforms, are then applied to the spatial series. These methods yield results compatible with traditional methods and show that it is useful for capturing transitions in cuspate shapes. To apply this new method, a land-based LIDAR study allowing for rapid high-resolution surveying is conducted on Melbourne Beach, Florida and Tairua Beach, New Zealand. Comparisons and testing of two different terrestrial scanning stations are evaluated during the course of the field investigation. Significant cusp activity is observed at Melbourne Beach. Morphological observations and sediment analysis are used to study beach cusp morphodynamics at the site. Surveys at Melbourne were run ~500 m alongshore and sediment samples were collected intertidally over a five-day period. Beach cusp location within larger scale beach morphology is shown to directly influence cusp growth as either predominantly erosional or accretional. Sediment characteristics within the beach cusp morphology are reported coincident with cusp evolution. Variations in pthesis size distribution kurtosis are exhibited as the cusps evolve; however, no significant correlation is seen between grain size and position between horn and embayment. During the end of the study, a storm resulted in beach cusp destruction and increased sediment sorting. In the former technique using multi-dimensional studies, a test of a new method for improving forecasting of surficial aquifer system water level changes with rainfall is conducted. The results provide a more rigorous analysis of common predictive techniques and compare them with the results of the tested model. These results show that linear interpretations of response-to-rainfall data require a clarification of how large events distort prediction and how the binning of data can change the interpretation. Analyses show that the binning ground water recharge data as is typically done in daily format may be useful for quick interpretation but only describes how fast the system responds to an event, not the frequency of return of such a response. Without a secure grasp on the nonlinear nature of water table and rainfall data alike, any binning or isolation of specific data carries the potential for aliasing that must be accounted for in an interpretation. The new model is proven capable of supplanting any current linear regression analysis as a more accurate means of prediction through the application of a multivariate technique. Furthermore, results show that in the Florida surficial aquifer system response-to-rainfall ratios exhibit a maxima most often linked with modal stage.

The safety of Powered Two Wheelers (PTWs) is important for public authorities and roadadministrators around the world. Recent official figures show that PTWs are estimated to represent only 2% of the total traffic but represent 30% of total deaths on French roads. However, as these estimated figures are obtained by simply counting the number plates registered, they do not give a true picture of the PTWs on the road at any given moment. This dissertation comes under the project METRAMOTO and is a technical applied research work and deals with two problems: detection of PTWsand the use of a laser scanner to count PTWs in the traffic. Traffic generally contains random vehicles of unknown nature and behaviour such as speed,vehicle interaction with other users on the road etc. Even though there are several technologies that can measure traffic, for example radars, cameras, magnetometers etc, as the PTWs are small-sized vehicles, they often move in between lanes and at quite a high speed compared to the vehicles moving in the adjacent lanes. This makes them difficult to detect. the proposed solution in this research work is composed of the following parts: a configuration to install the laser scanner on the road is chosen and a data coherence method is introduced so that the system is able to detect the road verges and its own height above the road surface. This is validated by simulator. Then the rawd ata obtained is pre-processed and is transform into the spatial temporal domain. Following this, an extraction algorithm called the Last Line Check (LLC) method is proposed. Once extracted, the objectis classified using one of the two classifiers either the Support Vector Machine (SVM) or the k-Nearest Neighbour (KNN). At the end, the results given by each of the two classifiers are compared and presented in this research work. The proposed solution in this research work is a propototype that is intended to be integrated in a real time system that can be installed on a highway to detect, extract, classify and counts PTWs in real time under all traffic conditions (traffic at normal speeds, dense traffic and even traffic jams).

La validation des algorithmes de tractographie et l’optimisation des paramètres choisis en référence à une vérité terrain, sont primordiales avant l’utilisation de ces méthodes en routine clinique. D’une part, nous présentons une méthode de comparaison quantitative de reconstructions issues de la tractographie à celles reconstruites depuis la dissection par un scanner laser. Cette comparaison permet d’évaluer les reconstructions de différents modèles et algorithmes de tractographie (déterministe, probabiliste) en les confrontant à une vérité terrain acquise par le scanner laser (surfaces triangulées). La transformation des données sous des formats communs était nécessaire avant leur comparaison quantitative. Deux méthodes de comparaison, surface-surface et volume-volume ont été proposées. D’autre part, nous présentons une méthode d’optimisation par algorithme génétique (AG), des paramètres de tractographie déterministe. L’AG est un algorithme itératif d’optimisation basé sur la sélection naturelle, il est capable d’optimiser des problèmes complexes ayant plusieurs paramètres. Etant donné la vérité terrain d’un faisceau, l’AG se propose de trouver le jeu de paramètres optimal donnant le meilleur résultat de tractographie. Les méthodes de comparaisons et d’optimisation ont été appliquées à un faisceau d’objet test puis à deux faisceaux disséqués à partir d’un cerveau humain post mortem après acquisitions IRM et scanner laser. / Tractography validation and optimization of tracking parameters against a ground truth are mandatory before a large clinical use. First, we present a method to quantitatively compare tractography reconstructions to a ground truth derived from laser scanner acquisitions of dissected specimens. This comparison allows evaluation of multiple models and tractography approaches (deterministic, probabilistic…). The ground truth used for this comparison was acquired from dissected specimens using a surface laser scanner, which produces triangulated surface meshes. Data transformation to a common format was necessary before quantitative comparisons. Two comparison methods were proposed, surface-to-surface and volume-to-volume. Second, we propose a method for automatic optimization of deterministic tractography parameters using a genetic algorithm (GA). The GA is an iterative optimization algorithm based on natural selection, which is able to optimize complex problems having several parameters. For a given ground truth fasciculus, the GA was expected to find the set of tractography parameters producing the best tractography result according to the ground truth. The comparison and optimization methods were applied to a synthetic bundle derived from a phantom and to two dissected white matter tracts of a human post mortem brain.

Depuis des décennies, les chercheurs essaient de développer des systèmes intelligents pour les véhicules modernes, afin de rendre la conduite plus sûre et plus confortable. Ces systèmes peuvent conduire automatiquement le véhicule ou assister un conducteur en le prévenant et en l'assistant en cas de situations dangereuses. Contrairement aux conducteurs, ces systèmes n'ont pas de contraintes physiques ou psychologiques et font preuve d'une grande robustesse dans des conditions extrêmes. Un composant clé de ces systèmes est la fiabilité de la perception de l'environnement. Pour cela, les capteurs lasers sont très populaires et largement utilisés. Les capteurs laser 2D classiques ont des limites qui sont souvent compensées par l'ajout d'autres capteurs complémentaires comme des caméras ou des radars. Les avancées récentes dans le domaine des capteurs, telles que les capteurs laser 3D qui perçoivent l'environnement avec une grande résolution spatiale, ont montré qu'ils étaient une solution intéressante afin d'éviter l'utilisation de plusieurs capteurs. Bien qu'il y ait des méthodes bien connues pour la perception avec des capteurs laser 2D, les approches qui utilisent des capteurs lasers 3D sont relativement rares dans la littérature. De plus, la plupart d'entre elles utilisent plusieurs capteurs et réduisent le problème de la 3ème dimension en projetant les données 3D sur un plan et utilisent les méthodes classiques de perception 2D. Au contraire de ces approches, ce travail résout le problème en utilisant uniquement un capteur laser 3D et en utilisant les informations spatiales fournies par ce capteur. Notre première contribution est une extension des méthodes génériques de cartographie 3D fondée sur des grilles d'occupations optimisées pour résoudre le problème de cartographie et de localisation simultanée (SLAM en anglais). En utilisant des grilles d'occupations 3D, nous définissons une carte d'élévation pour la segmentation des données laser correspondant au sol. Pour corriger les erreurs de positionnement, nous utilisons une méthode incrémentale d'alignement des données laser. Le résultat forme la base pour le reste de notre travail qui constitue nos contributions les plus significatives. Dans la deuxième partie, nous nous focalisons sur la détection et le suivi des objets mobiles (DATMO en anglais). La deuxième contribution de ce travail est une méthode pour distinguer les objets dynamiques des objets statiques. L'approche proposée utilise une détection fondée sur le mouvement et sur des techniques de regroupement pour identifier les objets mobiles à partir de la grille d'occupations 3D. La méthode n'utilise pas de modèles spécifiques d'objets et permet donc la détection de tout type d'objets mobiles. Enfin, la troisième contribution est une méthode nouvelle pour classer les objets mobiles fondée sur une technique d'apprentissage supervisée. La contribution finale est une méthode pour suivre les objets mobiles en utilisant l'algorithme de Viterbi pour associer les nouvelles observations avec les objets présents dans l'environnement, Dans la troisième partie, l'approche propose est testée sur des jeux de données acquis à partir d'un capteur laser 3D monté sur le toit d'un véhicule qui se déplace dans différents types d'environnement incluant des environnements urbains, des autoroutes et des zones piétonnes. Les résultats obtenus montrent l'intérêt du système intelligent proposé pour la cartographie et la localisation simultanée ainsi que la détection et le suivi d'objets mobiles en environnement extérieur et dynamique en utilisant un capteur laser 3D. / With an anticipation to make driving experience safer and more convenient, over the decades, researchers have tried to develop intelligent systems for modern vehicles. The intended systems can either drive automatically or monitor a human driver and assist him in navigation by warning in case of a developing dangerous situation. Contrary to the human drivers, these systems are not constrained by many physical and psychological limitations and therefore prove more robust in extreme conditions. A key component of an intelligent vehicle system is the reliable perception of the environment. Laser range finders have been popular sensors which are widely used in this context. The classical 2D laser scanners have some limitations which are often compensated by the addition of other complementary sensors including cameras and radars. The recent advent of new sensors, such as 3D laser scanners which perceive the environment at a high spatial resolution, has proven to be an interesting addition to the arena. Although there are well-known methods for perception using 2D laser scanners, approaches using a 3D range scanner are relatively rare in literature. Most of those which exist either address the problem partially or augment the system with many other sensors. Surprisingly, many of those rely on reducing the dimensionality of the problem by projecting 3D data to 2D and using the well-established methods for 2D perception. In contrast to these approaches, this work addresses the problem of vehicle perception using a single 3D laser scanner. First contribution of this research is made by the extension of a generic 3D mapping framework based on an optimized occupancy grid representation to solve the problem of simultaneous localization and mapping (SLAM). Using the 3D occupancy grid, we introduce a variance-based elevation map for the segmentation of range measurements corresponding to the ground. To correct the vehicle location from odometry, we use a grid-based incremental scan matching method. The resulting SLAM framework forms a basis for rest of the contributions which constitute the major achievement of this work. After obtaining a good vehicle localization and a reliable map with ground segmentation, we focus on the detection and tracking of moving objects (DATMO). The second contribution of this thesis is the method for discriminating between the dynamic objects and the static environment. The presented approach uses motion-based detection and density-based clustering for segmenting the moving objects from 3D occupancy grid. It does not use object specific models but enables detecting arbitrary traffic participants. Third contribution is an innovative method for layered classification of the detected objects based on supervised learning technique which makes it easier to estimate their position with time. Final contribution is a method for tracking the detected objects by using Viterbi algorithm to associate the new observations with the existing objects in the environment. The proposed framework is verified with the datasets acquired from a laser scanner mounted on top of a vehicle moving in different environments including urban, highway and pedestrian-zone scenarios. The promising results thus obtained show the applicability of the proposed system for simultaneous localization and mapping with detection, classification and tracking of moving objects in dynamic outdoor environments using a single 3D laser scanner.

A company wants to measure and verify the size of goods modules, transported on a conveyor belt, with the help of two 2D laser scanners (LMS100). The resulting measurements will be written to a database whereafter the modules will be moved by an automatic lifting device to a storage. The dimensions and possible any protrusions need to be known to avoid collision. The goal with this project is to write three modular libraries. One library for communicating with the LMS100 scanner, one library for calculating the dimensions of the goods modules and one library for handling the database. A graphical user interface (GUI) was also created which was implemented with an existing graphical library, Simple Directmedia Layer (SDL). A Raspberry Pi 3 has been used as a hardware platform which communicates with two LMS100 via ethernet. All code is written in the programming language C. LMS100 communicates with so called telegrams and the library implements these with TCP sockets. The structure of these can be found in the manufacturer’s datasheet. The calculating library uses trigonometric functions with measurement values from the scanners. The database library uses sqlite3 for a serverless database. The testing of these libraries was first done on a small scale with only one scanner and a small box placed a few decimeters in front of the scanner, to verify the functionality of the libraries. The company later provided a larger test rig with a remote controlled  platform, which drove between the scanners. When measuring objects with this test rig, the system showed an adequate ability to verify the size of the goods module. An inherent measurement error of a few millimeters of the scanners is shown, but this doesn’t affect the functionality in the final product which will measure considerably larger objects. Some functions are prepared for future development but aren’t yet ready for use. The protrusions of the goods modules aren’t yet discovered by the system. The calculating library is prepared to be able to detect these, but the evaluation of them aren’t ready. If the goods module is at an angle, the system measurements will be faulty. For every scanned segment the coordinates are saved and in future development it will be able to detect the angle. / Ett företag vill med hjälp av två stycken 2D-laserskannrar (LMS100) mäta och verifiera storleken på godsmoduler som transporteras på ett transportband. Mätresultatet ska skrivas till en databas varefter modulerna med en automatiskt styrd avlastare förflyttar dem till ett lager. Dimensioner och eventuella utstick på modulen måste vara kända för att undvika kollision. Målet med arbetet är att skriva tre stycken modulära bibliotek. Ett bibliotek för kommunikation med LMS100, ett bibliotek för beräkning av godsmodulens dimensioner och ett bibliotek för databashantering. Till detta skapades även ett grafiskt användargränssnitt (GUI) som implementerades med hjälp av ett färdigt grafikbibliotek, Simple Directmedia Layer (SDL).  En Raspberry Pi 3 har använts som hårdvaruplattform som kommunicerar med två stycken LMS100 via ethernetanslutning. All kod skrivs i programspråket C. LMS100 kommunicerar med s.k. telegram och biblioteket implementerar dessa via TCP sockets. Strukturen på dessa går att läsa i tillverkarens datablad. Beräkningsbiblioteket använder trigonometriska funktioner med mätvärden från skannrarna för beräkning. Databasbiblioteket använder sig av sqlite3 för en serverlös databas. Testning av dessa bibliotek skedde först på en småskalig nivå med endast en skanner och en liten låda placerad några decimeter framför skannern,  för att verifiera funktionaliteten på berörda bibliotek. Företaget bidrog senare med en testrig i större skala med en fjärrstyrd plattform, som körde mellan de två skannrarna. Vid mätning av objekt i denna testrig visade systemet en tillräckligt god förmåga för att kunna verifiera storlek på godsmoduler. Ett medföljt mätfel i millimeterskala finns i skannrarna, men detta påverkar inte funktionaliteten i den slutgiltiga produkten som ska mäta mycket större objekt. Vissa funktioner är förberedda för framtida utveckling men är inte färdiga för användning. Utstick på godsmodulerna upptäcks inte av systemet än. Beräkningsbiblioteket är förberett för att kunna upptäcka dessa, men utvärderingen av dem är inte färdigt. Om godsmodulen är vriden på transportbandet mäter systemet fel. Koordinater finns för varje skannat segment så att man ska kunna upptäcka denna vinkel i framtida utveckling.

The goal of this thesis is to scan part of castle Rokštejn using terrestrial laser scanner and from obtained data draw up a 3D model. Model is made with a method using meshing. In this work I also deal with the software, which supports meshing, and evaluating pros and cons of each program. The output of this work is 3D model which will serve to better representation of the current state of the castle and its better documentation.

The diploma thesis consists of two fundamental parts. The first part is focused on scanning a section of the Admas area by a terrestrial laser scanner. This section describes the introduction to laser scanning, necessary utilities and software, fieldwork, the process from the registration of a point cloud, through point cloud processing to its connection into the S-JTSK. The second part of the thesis is mostly focused on execution of the digital model of the relief from the acquired data. It also deals with the two methods of creating a cross-sectional drawing of the area - one is based on the digital model of the relief and the other on data obtained by the polar method. The outcome of the thesis is to assess the accuracy of the topographical model, based on the comparison with the polar method.

The goal of this thesis is to scan part of the complex research center AdMaS using terrestrial laser scanner, from obtained data draw up a 3D terrain model and compare the height accuracy with conventional terrestrial measurement. The thesis is focused to software, which allow processing of point clouds and prepare the 3D model. The output of this work is the 3D terrain model and two transverse profiles for vertical comparison of two measurement methods.

This thesis deals with design and implementation of extension module that enables 2D scanning with single-point interferometer. Afterwards is here solved question of software, which output data can be visualized in ModalVIEW by ABSignal company. My work also contains an overview of LDV sensors and scan systems, which are used to laser beam steering.

La sécurité des deux-roues motorisés (2RM) constitue un enjeu essentiel pour les pouvoirs publics et les gestionnaires routiers. Si globalement, l’insécurité routière diminue sensiblement depuis 2002, la part relative des accidents impliquant les 2RM a tendance à augmenter. Ce constat est résumé par les chiffres suivants : les 2RM représentent environ 2 % du trafic et 30 % des tués sur les routes.On observe depuis plusieurs années une augmentation du parc des 2RM et pourtant il manque des données et des informations sur ce mode de transport, ainsi que sur les interactions des 2RM avec les autres usagers et l'infrastructure routière. Ce travail de recherche appliquée est réalisé dans le cadre du projet ANR METRAMOTO et peut être divisé en deux parties : la détection des2RM et la détection des objets routiers par scanner laser. Le trafic routier en général contient des véhicules de nature et comportement inconnus, par exemple leurs vitesses, leurs trajectoires et leurs interactions avec les autres usagers de la route. Malgré plusieurs technologies pour mesurer le trafic,par exemple les radars ou les boucles électromagnétiques, il est difficile de détecter les 2RM à cause de leurs petits gabarits leur permettant de circuler à vitesse élevée et ce même en interfile. La méthode développée est composée de plusieurs sous-parties: Choisir une configuration optimale du scanner laser afin de l’installer sur la route. Ensuite une méthode de mise en correspondance est proposée pour trouver la hauteur et les bords de la route. Le choix d’installation est validé par un simulateur. A ces données brutes, la méthode de prétraitement est implémentée et une transformation de ces données dans le domaine spatio-temporel est faite. Après cette étape de prétraitement, la méthode d’extraction nommée ‘Last Line Check (LLC)’ est appliquée. Une fois que le véhicule est extrait, il est classifié avec un SVM et un KNN. Ensuite un compteur est mis en œuvre pour compter les véhicules classifiés. A la fin, une comparaison de la performance de chacun de ces deux classifieurs est réalisée. La solution proposée est un prototype et peut être intégrée dans un système qui serait installé sur une route au trafic aléatoire (dense, fluide, bouchons) pour détecter, classifier et compter des 2RM en temps réel. / The safety of Powered Two Wheelers (PTWs) is important for public authorities and roadadministrators around the world. Recent official figures show that PTWs are estimated to represent only 2% of the total traffic but represent 30% of total deaths on French roads. However, as these estimated figures are obtained by simply counting the number plates registered, they do not give a true picture of the PTWs on the road at any given moment. This dissertation comes under the project METRAMOTO and is a technical applied research work and deals with two problems: detection of PTWsand the use of a laser scanner to count PTWs in the traffic. Traffic generally contains random vehicles of unknown nature and behaviour such as speed,vehicle interaction with other users on the road etc. Even though there are several technologies that can measure traffic, for example radars, cameras, magnetometers etc, as the PTWs are small-sized vehicles, they often move in between lanes and at quite a high speed compared to the vehicles moving in the adjacent lanes. This makes them difficult to detect. the proposed solution in this research work is composed of the following parts: a configuration to install the laser scanner on the road is chosen and a data coherence method is introduced so that the system is able to detect the road verges and its own height above the road surface. This is validated by simulator. Then the rawd ata obtained is pre-processed and is transform into the spatial temporal domain. Following this, an extraction algorithm called the Last Line Check (LLC) method is proposed. Once extracted, the objectis classified using one of the two classifiers either the Support Vector Machine (SVM) or the k-Nearest Neighbour (KNN). At the end, the results given by each of the two classifiers are compared and presented in this research work. The proposed solution in this research work is a propototype that is intended to be integrated in a real time system that can be installed on a highway to detect, extract, classify and counts PTWs in real time under all traffic conditions (traffic at normal speeds, dense traffic and even traffic jams).