This paper presents an efficient metric for the computation of the similarity among omnidirectional images (image matching). The representation of image appearance is based on feature vectors that include both the chromatic attributes of color sets and their mutual spatial relationships. The proposed metric fits well to robotic navigation using omnidirectional vision sensors, because it has very important properties: it is reflexive, compositional and invariant with respect to image scaling and rotation. The robustness of the metric was repeatedly tested using omnidirectional images for a robot localization task in a real indoor environment.
An efficient similarity metric for omnidirectional vision sensors / Frontoni, Emanuele; Zingaretti, Primo. - In: ROBOTICS AND AUTONOMOUS SYSTEMS. - ISSN 0921-8890. - 54(9):(2006), pp. 750-757. [10.1016/j.robot.2006.04.014]
An efficient similarity metric for omnidirectional vision sensors
FRONTONI, EMANUELE;ZINGARETTI, PRIMO
2006-01-01
Abstract
This paper presents an efficient metric for the computation of the similarity among omnidirectional images (image matching). The representation of image appearance is based on feature vectors that include both the chromatic attributes of color sets and their mutual spatial relationships. The proposed metric fits well to robotic navigation using omnidirectional vision sensors, because it has very important properties: it is reflexive, compositional and invariant with respect to image scaling and rotation. The robustness of the metric was repeatedly tested using omnidirectional images for a robot localization task in a real indoor environment.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.