HAL will be down for maintenance from Friday, June 10 at 4pm through Monday, June 13 at 9am. More information
Skip to Main content Skip to Navigation
Journal articles

Urban accessibility diagnosis from mobile laser scanning data

Abstract : In this paper we present an approach for automatic analysis of urban acessibility using 3D point clouds. Our approach is based on range images and it consists in two main steps: urban objects segmentation and curbs detection. Both of them are required for accessibility diagnosis and itinerary planning. Our method automatically segments facades and urban objects using two hypotheses: facades are the highest vertical structures in the scene and objects are bumps on the ground on the range image. The segmentation result is used to build an urban obstacle map. After that, the gradient is computed on the ground range image. Curb candidates are selected using height and geodesic features. Then, nearby curbs are reconnected using Bézier curves. Finally, accessibility is defined based on geometrical features and accessibility standards. Our methodology is tested on two MLS databases from Paris (France) and Enschede (The Netherlands). Our experiments show that our method has good detection rates, is fast and presents few false alarms. Our method outperforms other works reported in the literature on the same databases.
Complete list of metadata

Cited literature [30 references]  Display  Hide  Download

Contributor : Andrés Serna Connect in order to contact the contributor
Submitted on : Saturday, March 22, 2014 - 12:07:56 PM
Last modification on : Wednesday, November 17, 2021 - 12:27:11 PM
Long-term archiving on: : Sunday, June 22, 2014 - 10:37:21 AM


Files produced by the author(s)



Andrés Serna, Beatriz Marcotegui. Urban accessibility diagnosis from mobile laser scanning data. ISPRS Journal of Photogrammetry and Remote Sensing, Elsevier, 2013, 84, pp.23-32. ⟨10.1016/j.isprsjprs.2013.07.001⟩. ⟨hal-00963820⟩



Record views


Files downloads