Generating compact meshes under planar constraints: an automatic approach for modeling buildings from aerial LiDAR

International audienceWe present an automatic approach for modeling buildings from aerial LiDAR data. The method produces accurate, watertight and compact meshes under planar constraints which are especially designed for urban scenes. The LiDAR point cloud is classified through a non-convex energy minimization problem in order to separate the points labeled as building. Roof structures are then extracted from this point subset, and used to control the meshing procedure. Experiments highlight the potential of our method in term of minimal rendering, accuracy and compactnes

City Reconstruction from Airborne Lidar: A Computational Geometry Approach

International audienceWe introduce a pipeline that reconstructs buildings of urban environments as concise polygonal meshes from airborne LiDAR scans.It consists of three main steps : classification, building contouring, and building reconstruction, the two last steps being achievedusing computational geometry tools. Our algorithm demonstrates its robustness, flexibility and scalability by producing accurateand compact 3D models over large and varied urban areas in a few minutes only

Probabilistic Temporal Inference on Reconstructed 3D Scenes

©2010 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.Presented at the 2010 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 13-18 June 2010, San Francisco, CA.DOI: 10.1109/CVPR.2010.5539803Modern structure from motion techniques are capable of building city-scale 3D reconstructions from large image collections, but have mostly ignored the problem of large-scale structural changes over time. We present a general framework for estimating temporal variables in structure from motion problems, including an unknown date for each camera and an unknown time interval for each structural element. Given a collection of images with mostly unknown or uncertain dates, we use this framework to automatically recover the dates of all images by reasoning probabilistically about the visibility and existence of objects in the scene. We present results on a collection of over 100 historical images of a city taken over decades of time

Semantic evaluation of 3D city models

The automatic generation of 3D urban models from geospa-tial data is now a standard procedure. However, practitioners still have to visually assess, at city-scale, the correctness of these models and detect inevitable reconstruction errors. Such a process relies on experts, and is highly time-consuming (2 h/km 2 /expert). In this work, we propose an approach for automatically evaluating the quality of 3D building models. Potential errors are compiled in a hierarchical, versatile and parameter-izable taxonomy. This allows for the first time to disentangle fidelity and modeling errors, whatever the level of details of the modeled buildings. The quality of models is predicted using the geometric properties of buildings and, when available, image and depth data. A baseline of handcrafted, yet generic features, is fed to a Random Forest classifier. Both multi-class and multi-label cases are considered. Due to the interdependence between classes of errors, we have the ability to retrieve all errors at the same time while predicting erroneous buildings. We tested our framework on an urban area with more than 1,000 building models. We can satisfactorily detect, on average 96% of the most frequent errors

A Featureless Approach to 3D Polyhedral Building Modeling from Aerial Images

This paper presents a model-based approach for reconstructing 3D polyhedral building models from aerial images. The proposed approach exploits some geometric and photometric properties resulting from the perspective projection of planar structures. Data are provided by calibrated aerial images. The novelty of the approach lies in its featurelessness and in its use of direct optimization based on image rawbrightness. The proposed framework avoids feature extraction and matching. The 3D polyhedral model is directly estimated by optimizing an objective function that combines an image-based dissimilarity measure and a gradient score over several aerial images. The optimization process is carried out by the Differential Evolution algorithm. The proposed approach is intended to provide more accurate 3D reconstruction than feature-based approaches. Fast 3D model rectification and updating can take advantage of the proposed method. Several results and evaluations of performance from real and synthetic images show the feasibility and robustness of the proposed approach

Modeling urban landscapes from point clouds: a generic approach

We present a robust method for modeling cities from 3D-point data. Our algorithm provides a more complete description than existing approaches by reconstructing simultaneously buildings, trees and topographically complex grounds. A major contribution of our work is the original way of modeling buildings which guarantees a high generalization level while having semantized and compact representations. Geometric 3D-primitives such as planes, cylinders, spheres or cones describe regular roof sections, and are combined with mesh-patches that represent irregular roof components. The various urban components interact through a non-convex energy minimization problem in which they are propagated under arrangement constraints over a planimetric map. Our approach is experimentally validated on complex buildings and large urban scenes of millions of points and compare it to state-of-the-art methods.Nous présentons une méthode robuste pour modéliser les villes à partir de nuages de points 3D. Notre algorithme fournit une description plus complète que les approches existantes en reconstruisant simultanément bâtiments, arbres et sols topographiquement complexes. Une des contributions importantes réside dans la manière originale de modéliser en 3D les bâtiments, garantissant un niveau de généralisation élevé tout en ayant une représentation compacte et sémantisée. Des primitive géométriques 3D telles que des plans, des cylindres, des sphères ou des cones décrivent les facettes de toit régulières. Elles sont combinées avec des parties de maillages qui représentent les composants de toits irréguliers. Les différents éléments urbains intéragissent au sein d'un problème de minimisation d'énergie non convexe dans lequel ils sont propagés sous des contraintes d'arrangement sur une carte planimétrique. L'approche est validée expérimentalement sur des bâtiments complexes et sur des scènes à grandes échelles contenant des millions de points, et comparée à des méthodes références