CMRT09

Stilla, Uwe

Bibliographic data

Monograph

Persistent identifier:: 856955019

Author:: Stilla, Uwe

Title:: CMRT09

Sub title:: object extraction for 3D city models, road databases, and traffic monitoring ; concepts, algorithms and evaluation ; Paris, France, September 3 - 4, 2009 ; [joint conference of ISPRS working groups III/4 and III/5]

Scope:: X, 234 Seiten

Year of publication:: 2009

Place of publication:: Lemmer

Publisher of the original:: GITC

Identifier (digital):: 856955019

Illustration:: Illustrationen, Diagramme, Karten

Language:: English

Usage licence:: Attribution 4.0 International (CC BY 4.0)

Publisher of the digital copy:: Technische Informationsbibliothek Hannover

Place of publication of the digital copy:: Hannover

Year of publication of the original:: 2016

Document type:: Monograph

Collection:: Earth sciences

Chapter

Title:: AN UNSUPERVISED HIERARCHICAL SEGMENTATION OF A FAÇADE BUILDING IMAGE IN ELEMENTARY 2D - MODELS Jean-Pascal Burochin, Olivier Tournaire and Nicolas Paparoditis

Document type:: Monograph

Structure type:: Chapter

«IMBiiìf* . ' : AN UNSUPERVISED HIERARCHICAL SEGMENTATION OF A FAÇADE BUILDING IMAGE IN ELEMENTARY 2D - MODELS Jean-Pascal Burochin, Olivier Tournaire and Nicolas Paparoditis Université Paris-Est, Institut Géographique National, Laboratoire MATIS 73 Avenue de Paris, 94165 Saint-Mandé Cedex, France {firstname.lastname} @ign.fr Commission III/3, III/4 KEY WORDS: street level imagery, façade reconstruction, unsupervised hierarchical segmentation, gradient accumulation, recursive split, model matching ABSTRACT: We introduce a new unsupervised segmentation method adapted to describe façade shapes from a single calibrated street level image. The image is first rectified thanks to its vanishing points to facilitate the extraction of façade main structures which are characterized by a horizontal and vertical gradient accumulation which enhances the detection of repetitive structures. Our aim is to build a hierarchy of rectangular regions bounded by the local maxima of the gradient accumulation. The algorithm recursively splits horizontally or vertically the image into two parts by maximizing the total length of regular edges until the radiometric content of the region hypothesis corresponds to a given model (planar and generalized cylinders). A regular edge is a segment of a main gradient direction that effectively matches to a contour of the image. This segmentation could be an interesting tool for façade modelling and is in particular well suited for façade texture compression. 1 INTRODUCTION 1.1 Context Façade analysis (detection, understanding and reconstruction) from street level imagery is currently a very active research do main in the photogrammetric computer vision field. Indeed, it has many applications. Façade models can for instance be used to increase the level of details of 3D city models generated from aerial or satellite imagery. They are also useful for a compact coding of façade image textures for streaming or for an embed ded system. The characterization of stable regions in façades is also necessary for a robust indexation and image retrieval. 1.2 Related work Existing façade extraction frameworks are frequently specialized for a certain type of architectural style or a given texture appear ance. In a procedural way, operators often step in a pre-process to split correctly the image in suitable regions. Studied images indeed are assumed to be framed in such a way that they exactly contain relevant information data such as windows on a clean wall background. Most building façade analysis techniques try to extract specific shapes/objects from the façade: windows frame, etc. Most of them are data driven, i.e. image features are first extracted and then some models are matched with them to build object hypothe ses. Some other model-driven techniques try to find more com plex objects which are patterns or layouts of simple objects (e.g. alignments in ID or in 2D). Higher level techniques try to gener ate directly a hierarchy of complex objects composed of patterns of simple objects usually with grammar-based approaches. Those methods generally devote their strategy to a special architectural style. 1.2.1 Single pattern detection Strategies to extract shape hy potheses abound in recent works. (Cech and Sara. 2007), for in stance, propose a segmentation based on a maximum a posteriori labeling. They associate each image pixel with values linked with some configuration rules. They extract a set of non-overlapping windowpanes hypotheses, assumed to form axis-parallel rectan gles of relatively low variability in appearance. This restriction does not take into account lighting variations. With a supervised classification-based approach, (Ali et al., 2007) extracted win dows width an adaboost algorithm. In the same fashion, (Wenzel and Forstner, 2008) minimize user interaction with a clustering procedure based on appearance similarity. Assuming the regularity of the façade, (Lee and Nevatia, 2004) use a gradient profile projection to locate window edges coordi nates. They first locate valley between two extrema blocks of each gradient accumulation profile and they roughly frame some floors and windows columns. Edges are then adjusted on local data information. Their results are relevant for façades whose background does not contain any contours such as railings, bal conies or cornices. 1.2.2 ID or 2D grid structures detection (Korah and Ras mussen, 2007, Reznik and Mayer, 2007) use linear primitives to generate rectangle hypotheses for windows. A Markov Random Field (MRF) is then used to constrain the hypotheses on a 2D regular grid. (Korah and Rasmussen. 2007) generate their rect angular hypotheses in a similar way as (Han and Zhu. 2005): they project on image 3D planar rectangles. (Reznik and Mayer. 2007) learn windows outline from training data and use as hy potheses for window corners characteristic points. 1.2.3 Façade grammars A façade grammar describes the spatial composition rules of complex objects (e.g. grid structure) and/or simple objects to construct a façade. Approaches based on grammars succeed in describing only façades corresponding to the grammar. Nevertheless, to obtain a detailed description a specific grammar is required per type of architecture (e.g. Haus- manian in the case of Parisian architecture). The drawback is that many grammars are necessary to describe the variety of building architectures in a general framework.

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