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:: BUILDING FOOTPRINT DATABASE IMPROVEMENT FOR 3D RECONSTRUCTION: A DIRECTION AWARE SPLIT AND MERGE APPROACH Bruno Vallet and Marc Pierrot-Deseilligny and Didier Boldo

Document type:: Monograph

Structure type:: Chapter

In: Stilla U, Rottensteiner F, Paparoditis N (Eds) CMRT09. IAPRS, Vol. XXXVIII, Part 3A/V4 — Paris, France, 3-4 September, 2009 BUILDING FOOTPRINT DATABASE IMPROVEMENT FOR 3D RECONSTRUCTION: A DIRECTION AWARE SPLIT AND MERGE APPROACH Bruno Vallet and Marc Pierrot-Deseilligny and Didier Boldo IGN - Laboratoire MATIS 2/4 avenue Pasteur - 94165 Saint-Mand Cedex, France bruno.vallet@ign.fr - http://recherche.ign.fr/labos/matis Commission III/3 KEY WORDS: Photogrammetry, 3D reconstruction, building footprint, split and merge, segmentation ABSTRACT: In the context of 3D reconstruction of wide urban areas, the use of building footprints has shown to be of great help to achieve both robustness and precision. These footprints however often present inconsistencies with the data (more than one building in the footprint, inner courts, superstructures...) This paper presents a fast and efficient algorithm to enhance the building footprint database in order to make subsequent 3D reconstructions easier, more accurate and more robust. It is based on a segmentation energy that is minimized by a split and merge approach. The algorithm is demonstrated on a wide urban area of one square kilometer. (a) Orthophotography and footprint (b) Shaded DEM and vegetation mask Figure 1 : Input to our algorithm 1 INTRODUCTION The production of 3D models of urban areas has received a lot of attention from the scientific community in the last decade be cause of the broad range of its applications and the increase in both quality and quantity of data. In this setup, it becomes more and more crucial to design flexible tools to help human operators achieving efficient and accurate reconstruction of wide urban ar eas. 1.1 Problem statement The problem of urban reconstruction consists in finding a 3D model (in general a polygonal surface) that is as coherent as pos sible with the input data. In our case where the footprints of the buildings are given, we can use the efficient and robust ap proach proposed in (Durupt and Taillandier, 2006). However, this approach relies heavily on the quality of the building foot print database, and might fail if the building to be reconstructed contains altimetric discontinuities that are not present in its foot print. This often happens in practice, and especially when: • Two (or more) adjacent buildings with different roof heights share the same footprint. • The real footprint of a building is only a portion of the foot print in the database (gardens, inner courts,...) • The building has some superstructures which sizes and heights are not negligeable with respect to the expected precision of the reconstruction. This problem becomes increasingly dif ficult as reconstructions gain in precision, and has already been tackled in the context of photogrammetry (Bredif et al„ 2007) (Domaika and Bredif, 2008). More difficult cases are often a combination of the three cited above, and require a manual intervention to enable a further re construction. In general, this intervention consists in subdividing the footprint by cutting through all (or most of) the altimetric dis continuities. In a production framework, where large areas need to be extensively reconstructed, it appears that this building foot print database enhancement step is one of the most time consum ing. Hence, the problem that we tackle in this paper is that of automatizing this enhancement as a required preprocessing step to 3D reconstruction. More precisely, our problem is to segment a polygonal footprint into a set of non-overlapping polygonal sub footprints that cover it entirely, such that the interface between the sub-footprints corresponds to altimetric discontinuities. This is a problem of segmentation of vector data (building footprints database) guided by raster data (photos, DEM,...) 1.2 Available data The data available in our study mainly consisted of: • A set of 10 centimeter resolution aerial images with a high recovery ratio around 60% (intraband + interband) in order to ensure that each ground point is seen in at least 4 images, covering an area of one square kilometer. The images are in RGBI (the infrared channel is used to obtain the vegetation mask). • A vectorized cadastral map giving building footprints for the same area. It consists in a set of polygonal footprints given by their ordered list of points in ground coordinates (Figure 1 (a), green). From this initial data, existing algorithms can be run to extract:

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