eprintid: 13703
rev_number: 19
eprint_status: archive
userid: 1903
dir: disk0/00/01/37/03
datestamp: 2012-11-20 10:37:41
lastmod: 2016-04-21 13:02:07
status_changed: 2012-11-20 10:37:41
type: conference_item
metadata_visibility: show
item_issues_count: 0
creators_name: Puente Yusty, Paloma de la
creators_name: Censi, Andrea
title: Dense Map Inference with User-Defined Priors: From Priorlets to Scan Eigenvariations
ispublished: pub
subjects: industrial
subjects: informatica
abstract: When mapping is formulated in a Bayesian framework, the need of specifying a prior for the environment arises naturally. However, so far, the use of a particular structure prior has been coupled to working with a particular representation. We describe a system that supports inference with multiple priors while keeping the same dense representation. The priors are rigorously described by the user in a domain-specific language. Even though we work very close to the measurement space, we are able to represent structure constraints with the same expressivity as methods based on geometric primitives. This approach allows the intrinsic degrees of freedom of the environment’s shape to be recovered. Experiments with simulated and real data sets will be presented
date: 2012
date_type: published
publisher: Springuer
full_text_status: public
pres_type: paper
volume: 7463
place_of_pub: Alemania
pagerange: 94-113
event_title: Spatial Cognition VIII
event_location: Kloster Seeon, Bavaria, Alemania
event_dates: 01/09/2012 - 03/09/2012
event_type: conference
institution: Industriales
department: Automatica
refereed: TRUE
isbn: 978-3-642-32732-2_6
book_title: Spatial Cognition VIII. Lecture Notes in Computer Science
rights: by-nc-nd
citation:    Puente Yusty, Paloma de la and Censi, Andrea  (2012).  Dense Map Inference with User-Defined Priors: From Priorlets to Scan Eigenvariations.  In: "Spatial Cognition VIII", 01/09/2012 - 03/09/2012, Kloster Seeon, Bavaria, Alemania. ISBN 978-3-642-32732-2_6. pp. 94-113.    
document_url: https://oa.upm.es/13703/2/INVE_MEM_2012_115628.pdf