On precise three-dimensional environment modeling via UAV-based photogrammetric systems

Abstract : Images acquired from unmanned aerial vehicles (UAVs) can provide data with unprecedented spatial and temporal resolution for three-dimensional (3D) modeling. Solutions developed for this purpose are mainly operating based on photogrammetry concepts, namely UAV-Photogrammetry Systems (UAV-PS). Such systems are used in applications where both geospatial and visual information of the environment is required. These applications include, but are not limited to, natural resource management such as precision agriculture, military and police-related services such as traffic-law enforcement, precision engineering such as infrastructure inspection, and health services such as epidemic emergency management. UAV-photogrammetry systems can be differentiated based on their spatial characteristics in terms of accuracy and resolution. That is some applications, such as precision engineering, require high-resolution and high-accuracy information of the environment (e.g. 3D modeling with less than one centimeter accuracy and resolution). In other applications, lower levels of accuracy might be sufficient, (e.g. wildlife management needing few decimeters of resolution). However, even in those applications, the specific characteristics of UAV-PSs should be well considered in the steps of both system development and application in order to yield satisfying results. In this regard, this thesis presents a comprehensive review of the applications of unmanned aerial imagery, where the objective was to determine the challenges that remote-sensing applications of UAV systems currently face. This review also allowed recognizing the specific characteristics and requirements of UAV-PSs, which are mostly ignored or not thoroughly assessed in recent studies. Accordingly, the focus of the first part of this thesis is on exploring the methodological and experimental aspects of implementing a UAV-PS. The developed system was extensively evaluated for precise modeling of an open-pit gravel mine and performing volumetric-change measurements. This application was selected for two main reasons. Firstly, this case study provided a challenging environment for 3D modeling, in terms of scale changes, terrain relief variations as well as structure and texture diversities. Secondly, open-pit-mine monitoring demands high levels of accuracy, which justifies our efforts to improve the developed UAV-PS to its maximum capacities. The hardware of the system consisted of an electric-powered helicopter, a high-resolution digital camera, and an inertial navigation system. The software of the system included the in-house programs specifically designed for camera calibration, platform calibration, system integration, onboard data acquisition, flight planning and ground control point (GCP) detection. The detailed features of the system are discussed in the thesis, and solutions are proposed in order to enhance the system and its photogrammetric outputs. The accuracy of the results was evaluated under various mapping conditions, including direct georeferencing and indirect georeferencing with different numbers, distributions and types of ground control points. Additionally, the effects of imaging configuration and network stability on modeling accuracy were assessed. The second part of this thesis concentrates on improving the techniques of sparse and dense reconstruction. The proposed solutions are alternatives to traditional aerial photogrammetry techniques, properly adapted to specific characteristics of unmanned, low-altitude imagery. Firstly, a method was developed for robust sparse matching and epipolar-geometry estimation. The main achievement of this method was its capacity to handle a very high percentage of outliers (errors among corresponding points) with remarkable computational efficiency (compared to the state-of-the-art techniques). Secondly, a block bundle adjustment (BBA) strategy was proposed based on the integration of intrinsic camera calibration parameters as pseudo-observations to Gauss-Helmert model. The principal advantage of this strategy was controlling the adverse effect of unstable imaging networks and noisy image observations on the accuracy of self-calibration. The sparse implementation of this strategy was also performed, which allowed its application to data sets containing a lot of tie points. Finally, the concepts of intrinsic curves were revisited for dense stereo matching. The proposed technique could achieve a high level of accuracy and efficiency by searching only through a small fraction of the whole disparity search space as well as internally handling occlusions and matching ambiguities. These photogrammetric solutions were extensively tested using synthetic data, close-range images and the images acquired from the gravel-pit mine. Achieving absolute 3D mapping accuracy of 11±7 mm illustrated the success of this system for high-precision modeling of the environment.

Exploration des réseaux de neurones à base d'autoencodeur dans le cadre de la modélisation des données textuelles

Depuis le milieu des années 2000, une nouvelle approche en apprentissage automatique, l'apprentissage de réseaux profonds (deep learning), gagne en popularité. En effet, cette approche a démontré son efficacité pour résoudre divers problèmes en améliorant les résultats obtenus par d'autres techniques qui étaient considérées alors comme étant l'état de l'art. C'est le cas pour le domaine de la reconnaissance d'objets ainsi que pour la reconnaissance de la parole. Sachant cela, l’utilisation des réseaux profonds dans le domaine du Traitement Automatique du Langage Naturel (TALN, Natural Language Processing) est donc une étape logique à suivre. Cette thèse explore différentes structures de réseaux de neurones dans le but de modéliser le texte écrit, se concentrant sur des modèles simples, puissants et rapides à entraîner.

Journalisation dans un Programme de carrière en nouveaux médias : Le rôle de la réflexion par l’action

The purpose of this case study is to report on the use of learning journals as a strategy to encourage critical reflection in the field of graphic design. Very little empirical research has been published regarding the use of critical reflection in learning journals in this field. Furthermore, nothing has been documented at the college level. To that end, the goal of this research endeavor was to investigate whether second-year students in the NewMedia and Publication Design Program at a small Anglophone CEGEP in Québec, enrolled in a Page Layout and Design course, learn more deeply by reflecting in action during design projects or reflecting on action after completing design projects. Secondarily, indications of a possible change in self-efficacy were examined. Two hypotheses were posited: 1) reflection-on-action journaling will promote a deeper approach to learning than reflection-in-action journaling, and 2) the level of self-efficacy in graphic design improves as students are encouraged to think reflectively. Using both qualitative and quantitative methods, a mixed methods approach was used to collect and analyze the data. Content analysis of journal entries and interview responses was the primary method used to address the first hypothesis. Students were required to journal twice for each of three projects, once during the project and again one week after the project had been submitted. In addition, data regarding the students' perception of journaling was obtained through administering a survey and conducting interviews. For the second hypothesis, quantitative methods were used through the use of two surveys, one administered early in the Fall 2011 semester and the second administered early in the Winter 2012 semester. Supplementary data regarding self-efficacy was obtained in the form of content analysis of journal entries and interviews. Coded journal entries firmly supported the hypothesis that reflection-on-action journaling promotes deep learning. Using a taxonomy developed by Kember et al. (1999) wherein "critical reflection" is considered the highest level of reflection, it was found that only 5% of the coded responses in the reflection-in-action journals were deemed of the highest level, whereas 39% were considered critical reflection in the reflection-on-action journals. The findings from the interviews suggest that students had some initial concerns about the value of journaling, but these concerns were later dismissed as students learned that journaling was a valuable tool that helped them reflect and learn. All participants indicated that journaling changed their learning processes as they thought much more about what they were doing while they were doing it. They were taking the learning they had acquired and thinking about how they would apply it to new projects; this is critical reflection. The survey findings did not support the conclusive results of the comparison of journal instruments, where an increase of 35% in critical reflection was noted in the reflection-on-action journals. In Chapter 5, reasons for this incongruence are explored. Furthermore, based on the journals, surveys, and interviews, there is not enough evidence at this time to support the hypothesis that self-efficacy improves when students are encouraged to think reflectively. It could be hypothesized, however, that one's self-efficacy does not change in such a short period of time. In conclusion, the findings established in this case study make a practical contribution to the literature concerning the promotion of deep learning in the field of graphic design, as this researcher's hypothesis was supported that reflection-on-action journaling promoted deeper learning than reflection-in-action journaling. When examining the increases in critical reflection from reflection-in-action to the reflection-on-action journals, it was found that all students but one showed an increase in critical reflection in reflection-on-action journals. It is therefore recommended that production-oriented program instructors consider integrating reflection-on-action journaling into their courses where projects are given.