ROBUST METHODS FOR ROBOT LOCALIZATION UNDER CHANGING ILLUMINATION CONDITIONS. Comparison of Different Filtering Techniques
Lorenzo FernŠndez Rojo, Luis PayŠ, Oscar Reinoso, Arturo Gil and Miguel JuliŠ
ICAART 2010. 2ļ INTERNATIONAL CONFERENCE ON AGENTS AND ARTIFICIAL INTELLIGENCE  (Valencia, Spain. 22-24 January, 2010)
Ed. Edited by Joaquim Filipe, Ana Fred and Bernadette Sharp  ISBN:978-989-674-021-4  - Volume 1. pp 223-228

Resumen:

The use of omnidirectional systems provides us with rich visual information that allows us to create
appearance-based dense maps. This map can be composed of several panoramic images taken from different
positions in the environment. When the map contains only visual information, it will depend heavily on the
conditions of the environment lighting. Therefore we get different visual information depending on the time
of day when the map is created, the state of artificial lighting in the environment, or any other circumstance
that causes a change in the illumination of the scene. To obtain a robust map against changes in the
illumination of the environment we apply different filters on the panoramic images. After that, we use some
compression methods that allow us to reduce the amount of information stored. We have conducted a
comprehensive experimentation to study which type of filter best adapts to changing lighting conditions.