No description available.

This thesis is in the field of computer vision, focusing on the problems of optical flow estimation. Optical flow is a notoriously difficult 2D problem since it’s inherently underconstrained. To introduce the concept of cyclopean optical flow, we will downgrade the 2D into 1D to make it more accessible. It proposes a new approach based on a "cyclopean" frame of reference. We apply a constrained gradient-based technique to solve 1D optical flow, for which the constraints are gradient behavior and correlation score. This thesis focuses on the fundamental problem of ensuring that the gradient remains usable in an interval large enough to cover the spatial displacement of motion. The proposed "cyclopean" approach does not enforce optical measurements over a fixed grid, which results in more reliable results. To further increase the allowed motion interval, we propose a pyramidal constraint that allows solving over a coarse-to-fine approach. We solved over aerial imagery, Sintel data-set, and Sintel data-set when artificially displaced 10% of the ground truth. This work is developed in the "continuous" framework commonly used for small motion optical flow. Our results showed good management of false positives while maintaining a good amount of convergence density. However, our method isn’t as precise as the current state-of-the-art benchmarks, as it specializes in very small motions. Also, it’s important to mention versatility comes with the concept of "continuous" representation. This allows us to select regions to be solved, opening the possibility of adapting to the spectrum of sparse or dense optical flow. From this study point of view, we can highlight traditional methods have relevance even in the deep learning era, offering a new set of tools to exploit on the pursue of solving optical flow. / Ce mémoire s’intéresse au domaine de la vision par ordinateur, et plus particulièrement l’estimation du flux optique. Le flux optique est un problème 2D notoirement difficile, car il est intrinsèquement sous-contraint. Pour introduire la notion de flux optique cyclopéen, nous allons considérer le problème en 1D pour éliminer le problème d’ouverture lié au mouvement 2D. Nous proposons une nouvelle approche basée sur un référentiel « cyclopéen », basée sur gradient calculé dans un espace continu pour résoudre le flux optique 1D. Ce mémoire se concentre a garantir que le gradient reste utilisable dans un intervalle suffisamment grand pour couvrir le déplacement spatial du mouvement. Lors de la résolution sur une approche coarse-to-fine, une représentation pyramidale est utilisée. Les résultats sur des images aériennes ainsi que des données synthétiques sont prometteurs. Ce travail se distingue des tendances actuelles en flux optique parle fait qu’il se spécialise pour les flux optiques à faible mouvement. Nos résultats ont montré une bonne gestion des faux positifs tout en conservant une bonne densité. Nous considérons que la fiabilité des mesures de mouvement est très élevée, ce qui est au moins aussi important que la précision elle-même dans beaucoup d’applications. Ainsi, la polyvalence de la représentation "continue" permet de mieux contrôler la densité obtenue en fonction de la scène analysée. À notre avis, cette approche, qui complète les méthodes traditionnelles, ouvrira la voie à de nouvelles approches en apprentissage profond.

No description available.

No description available.

No description available.

Semi-autonomous uncrewed aerial vehicles (UAVs) are telerobotic operations by definition where the UAV assumes the role of a telerobot and the human assumes the role of a supervisor. All telerobotic operations are susceptible to time delays due to communication, mechanical, and other constraints. Typically, these delays are small and do not affect the telerobotic operation for most of the tasks. However, for long-distance telerobotic operations like interplanetary rovers, deep underwater vehicles, etc. the delays can be so significant that they can render the entire operation void. This dissertation investigates the use of a novel heterogeneous stereo-vision system to mitigate the effects of time delays in a UAV-based visual interface presented to a human operator. The heterogeneous stereo-vision system consists of an omnidirectional camera and a pan-tilt-zoom camera. Two predictive display setups were developed that modify the delayed video imagery that would otherwise be presented to the operator in a way that provides an almost immediate visual response to the operator's control actions. The usability of the system is determined through human performance testing with and without the predictive algorithms. The results indicate that the predictive algorithm allows more efficient, accurate, and user-friendly operation. The second half of the dissertation deals with improving the performance of the predictive display and expanding the concept of the prediction from a stationary gimbal-camera system to a moving 6 DoF aircraft. Specifically, it talks about a novel extended Kalman filter (EKF)-based nonlinear predictor – the extended Kalman predictor (EKP) – and compares its performance with two linear predictors, the Smith predictor (SP) and the Kalman predictor (KP). This dissertation provides the mathematical formulation of the EKP, as well as the two linear predictors, and describes their use with simulated flight data obtained using a nonlinear motion model for a small, fixed-wing UAV. The EKP performs comparably to the KP when the aircraft motion experiences small perturbations from a nominal trajectory, but the EKP outperforms the KP for larger excursions. The SP performs poorly in every case. / Doctor of Philosophy / Semi-autonomous uncrewed aerial vehicles (UAVs) are telerobotic operations by definition where the aerial vehicle assumes the role of a telerobot and the human assumes the role of a supervisor. This dissertation addresses the challenges posed by time delays in uncrewed aerial vehicle operations, particularly for long-distance operations such as interplanetary exploration and deep-sea missions. It investigates the use of a novel heterogeneous stereo-vision system to mitigate these delays, providing operators with nearly real-time visual feedback. Human performance testing confirms the predictive algorithm allows more efficient, accurate, and user-friendly operation. Additionally, the dissertation presents advancements in the predictive display performance for moving UAVs with six degrees of freedom. It introduces a novel extended Kalman predictor and compares it to traditional linear predictors like the Smith predictor and the Kalman predictor using simulated flight data. The extended Kalman predictor demonstrates superior performance for larger deviations from trajectory, highlighting its effectiveness in predicting the motion of an aircraft when there are time delays present.

No description available.

No description available.

This thesis addresses a number of problems in computer vision, image processing, and geometry processing, and presents novel solutions to these problems. The overarching theme of the techniques presented here is a multi-scale approach, leveraging mathematical tools to represent images and surfaces at different scales, and methods that can be adapted from one type of domain (eg., the plane) to another (eg., the sphere). The main problem addressed in this thesis is known as stereo reconstruction: reconstructing the geometry of a scene or object from two or more images of that scene. We develop novel algorithms to do this, which work for both planar and spherical images. By developing a novel way to formulate the notion of disparity for spherical images, we are able effectively adapt our algorithms from planar to spherical images. Our stereo reconstruction algorithm is based on a novel application of distance transforms to multi-scale matching. We use matching information aggregated over multiple scales, and enforce consistency between these scales using distance transforms. We then show how multiple spherical disparity maps can be efficiently and robustly fused using visibility and other geometric constraints. We then show how the reconstructed point clouds can be used to synthesize a realistic sequence of novel views, images from points of view not captured in the input images, in real-time. Along the way to this result, we address some related problems. For example, multi-scale features can be detected in spherical images by convolving those images with a filterbank, generating an overcomplete spherical wavelet representation of the image from which the multiscale features can be extracted. Convolution of spherical images is much more efficient in the spherical harmonic domain than in the spatial domain. Thus, we develop a GPU implementation for fast spherical harmonic transforms and frequency domain convolutions of spherical images. This tool can also be used to detect multi-scale features on geometric surfaces. When we have a point cloud of a surface of a particular class of object, whether generated by stereo reconstruction or by some other modality, we can use statistics and machine learning to more robustly estimate the surface. If we have at our disposal a database of surfaces of a particular type of object, such as the human face, we can compute statistics over this database to constrain the possible shape a new surface of this type can take. We show how a statistical spherical wavelet shape prior can be used to efficiently and robustly reconstruct a face shape from noisy point cloud data, including stereo data.

Le travail présenté dans cette thèse vise à comprendre les vibrations de pièce mince durant l’usinage. De nombreux travaux proposent des modélisations de ce phénomène, mais des écarts persistent entre résultats de modélisation et réalité. Ce constat nous pousse à nous interroger sur l’emploi dans les modèles des modes propres de la pièce, sans y intégrer le contact de l’outil. Face à l’incapacité de vérifier la validité de cette hypothèse par mesures ponctuelles, la mesure de champ s’impose comme une alternative prometteuse. La deuxième partie du travail porte sur la mise au point d’un protocole expérimental novateur. Il inclut le relevé des déformées vibratoires d’une pièce mince en usinage par mesure de champs de déplacements. La stéréo corrélation d’images numériques se confronte à de nombreuses limitations dans ce contexte. Nous avons développé une méthode de réglage des capteurs permettant de contourner rapidement certaines difficultés. Cette méthode présentée sous forme graphique souligne la nécessité d’optimiser les paramètres de mesure dans un tel contexte. La troisième partie met en oeuvre le protocole de mesures. Le test des capteurs montre le fort intérêt de la mesure sans contact vis-à-vis de l’objectif recherché. Des essais d’usinage sont présentés en se basant sur une modélisation existante du broutement. Les déformées mesurées pendant l’usinage livrent des informations d’un type nouveau. Leur exploitation a impliqué la mise en place d’une procédure spécifique de traitement. La dernière partie présente les analyses de deux usinages. L’étude est effectuée au regard des états de surface obtenus, du comportement temporel, fréquentiel, et spatial. Cette approche souligne les subtilités de la génération d’état de surface en la présence de vibrations. L’examen des mesures de champs permet de relever des incohérences avec l’emploi des modes propres, classiquement utilisés en modélisation. / The work presented in this thesis aims at understanding thin part vibrations during machining. Many works propose modelings of this phenomenon but differencies still exist between modeling results and tests. This observation lead us to wonder about the employment of natural modes of the part in the models, without taking into account the tool presence. The fact that punctual measurements don’t enable to verify the validity of this hypothesis, field measurement prove to be a hopeful alternative. The second part focuses on adjusting a novel experimental protocol. It includes the recording of the thin part vibrating shapes by displacement field measurement. Digital Image Stereo Correlation is confronted to many limitations in this context. We developed a method to set sensors enabling the quick avoidance of difficulties. This method is presented in a graphical form, and underlines the need of optimising measurement parameters in such an environment. In the third part of the work, the measurement protocol is used. The sensors testing shows the high interest of contactless measurement for the aimed goal. Machininng tests are presented in connection with an existing model of chatter. The measured shapes during machining give a new sort of informations. So, their analyse implied the building of a specific processing procedure. The last part presents analyses of two machining tests. The study is done by parallely looking at the machined surface, and the behavior in temporal and frequency space as so as the part displacement fields. This approach underlines subtleties of surface generation under vibration conditions. The fields inspection enables to mark inconsistencies if employing the natural modes that are classically used in models.