Información del artículo
Resumen
El objetivo de este artículo es encontrar un extractor de características visuales que pueda ser utilizado en un proceso de SLAM (Simultaneous Localization and Mapping). Este extractor de características consiste en la combinación de un detector que extrae puntos significativos del entorno, y un descriptor local que caracteriza dichos puntos. Este artículo presenta la comparación de un conjunto de detectores de puntos de interés y de descriptores locales que se utilizan como marcas visuales en un proceso de SLAM. El análisis comparativo se divide en dos fases diferenciadas: detección y descripción. Se evalúa la repetibilidad de los detectores, así como la invariabilidad de los descriptores ante cambios de vista, escala e iluminación. Los experimentos se han realizado a partir de un conjunto de secuencias de imágenes tanto interiores (entorno de oficinas) como exteriores, con diversas variaciones en la imagen (iluminación y posición), representando así de una forma bastante general los entornos típicos de un robot. Se considera que los resultados de este trabajo pueden ser útiles a la hora de seleccionar una marca adecuada en SLAM visual, tanto para entornos interiores como exteriores.
Palabras clave:
SLAM visual
marcas visuales
detectores de puntos de interés
descriptores locales
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