Authors:
Lorenzo Fernández Rojo
1
;
Luis Payá
1
;
Oscar Reinoso
2
;
Arturo Gil
2
and
Miguel Juliá
2
Affiliations:
1
Miguel Hernandez University, Spain
;
2
Miguel Hernández University, Spain
Keyword(s):
Omnidirectional vision, Robot mapping, Appearance-based methods, Robust localization and illumination effects filtering.
Related
Ontology
Subjects/Areas/Topics:
Agents
;
Artificial Intelligence
;
Autonomous Systems
;
Biomedical Engineering
;
Biomedical Signal Processing
;
Data Manipulation
;
Health Engineering and Technology Applications
;
Human-Computer Interaction
;
Methodologies and Methods
;
Neurocomputing
;
Neurotechnology, Electronics and Informatics
;
Pattern Recognition
;
Physiological Computing Systems
;
Sensor Networks
;
Soft Computing
;
Vision and Perception
Abstract:
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.