Low-rank Based Algorithms for Rectification, Repetition Detection and De-noising in Urban Images

In this thesis, we aim to solve the problem of automatic image rectification and repeated patterns detection on 2D urban images, using novel low-rank based techniques. Repeated patterns (such as windows, tiles, balconies and doors) are prominent and significant features in urban scenes. Detection of the periodic structures is useful in many applications such as photorealistic 3D reconstruction, 2D-to-3D alignment, facade parsing, city modeling, classification, navigation, visualization in 3D map environments, shape completion, cinematography and 3D games. However both of the image rectification and repeated patterns detection problems are challenging due to scene occlusions, varying illumination, pose variation and sensor noise. Therefore, detection of these repeated patterns becomes very important for city scene analysis. Given a 2D image of urban scene, we automatically rectify a facade image and extract facade textures first. Based on the rectified facade texture, we exploit novel algorithms that extract repeated patterns by using Kronecker product based modeling that is based on a solid theoretical foundation. We have tested our algorithms in a large set of images, which includes building facades from Paris, Hong Kong and New York

Segmentation d'images de façades de bâtiments acquises d'un point de vue terrestre

L'analyse de façades (détection, compréhension et reconstruction) à partir d'images acquises depuis la rue est aujourd'hui un thème de recherche très actif en photogrammétrie et en vision par ordinateur de part ses nombreuses applications industrielles. Cette thèse montre des avancées réalisées dans le domaine de la segmentation générique de grands volumes de ce type d'images, contenant une ou plusieurs zones de façades (entières ou tronquées).Ce type de données se caractérise par une complexité architecturale très riche ainsi que par des problèmes liés à l'éclairage et au point de vue d'acquisition. La généricité des traitements est un enjeu important. La contrainte principale est de n'introduire que le minimum d'a priori possible. Nous basons nos approches sur les propriétés d'alignements et de répétitivité des structures principales de la façade. Nous proposons un partitionnement hiérarchique des contours de l'image ainsi qu'une détection de grilles de structures répétitives par processus ponctuels marqués. Sur les résultats, la façade est séparée de ses voisines et de son environnement (rue, ciel). D'autre part, certains éléments comme les fenêtres, les balcons ou le fond de mur, sans être reconnus, sont extraits de manière cohérente. Le paramétrage s'effectue en une seule passe et s'applique à tous les styles d'architecture rencontrés. La problématique se situe en amont de nombreuses thématiques comme la séparation de façades, l'accroissement du niveau de détail de modèles urbains 3D générés à partir de photos aériennes ou satellitaires, la compression ou encore l'indexation à partir de primitives géométriques (regroupement de structures et espacements entre ellesFacade analysis (detection, understanding and field of reconstruction) in street level imagery is currently a very active field of research in photogrammetric computer vision due to its many applications. This thesis shows some progress made in the field of generic segmentation of a broad range of images that contain one or more facade areas (as a whole or in part).This kind of data is carecterized by a very rich and varied architectural complexity and by problems in lighting conditions and in the choice of a camera's point of view. Workflow genericity is an important issue. One significant constraint is to be as little biased as possible. The approches presented extract the main facade structures based on geometric properties such as alignment and repetitivity. We propose a hierarchic partition of the image contour edges and a detection of repetitive grid patterns based on marked point processes. The facade is set appart from its neighbooring façades and from its environment (the ground, the sky). Some elements such as windows, balconies or wall backgrounds, are extracted in a relevant way, without being recognized. The parameters regulation is done in one step and refers to all architectural styles encountered. The problem originates from most themes such as facade separation, the increase of level of details in 3D city models generated from aerial or satellite imagery, compression or indexation based on geometric primitives (structure grouping and space between them)PARIS-EST-Université (770839901) / SudocSudocFranceF