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
Conference papers

Assessing Map Quality using Conditional Random Fields

Abstract : This paper is concerned with assessing the quality of work-space maps. While there has been much work in recent years on building maps of ¯eld settings, little attention has been given to endowing a machine with introspective competencies which would allow assessing the reliability/plausibility of the representation. We classify regions in 3D point-cloud maps into two binary classes|\plausible" or \suspicious". In this paper we concentrate on the classi¯cation of urban maps and use a Conditional Random Fields to model the intrinsic qualities of planar patches and crucially, their relationship to each other. A bipartite labelling of the map is acquired via application of the Graph Cut algorithm. We present results using data gathered by a mobile robot equipped with a 3D laser range sensor while operating in a typical urban setting.
Document type :
Conference papers
Complete list of metadata

Cited literature [20 references]  Display  Hide  Download

https://hal.inria.fr/inria-00201216
Contributor : Inria Rhône-Alpes Documentation Connect in order to contact the contributor
Submitted on : Thursday, December 27, 2007 - 10:49:45 AM
Last modification on : Monday, January 14, 2008 - 3:12:01 PM
Long-term archiving on: : Thursday, September 27, 2012 - 1:25:37 PM

File

fsr_75.pdf
Files produced by the author(s)

Identifiers

  • HAL Id : inria-00201216, version 1

Collections

Citation

Manjari Chandran-Ramesh, Paul Newman. Assessing Map Quality using Conditional Random Fields. 6th International Conference on Field and Service Robotics - FSR 2007, Jul 2007, Chamonix, France. ⟨inria-00201216⟩

Share

Metrics

Record views

52

Files downloads

168