Scene Recognition Invariant to Symetrical Reflections and Illumintation Conditions in Robotics

Scene understanding is still an important challenge in robotics. In this paper we analyse the impact of several global and local image representations to solve the task of scene recognition. The performance of the different alternatives were compared using a two benchmarks of images: (a) the public database KTH_IDOL and, (b) a base of images taken in the Centro Singular de Investigacion en Tecnoloxias da Informacion (CITIUS), at the University of Santiago de Compostela. The results are promising not only regarding the accuracy achieved, but mostly because we have found a combination of an holistic representation and local information that allows a correct classification of images robust to specular reflections, illumination conditions, changes of viewpoint, etc.

keywords: Scene recognition, Holistic representations, Local representations, Invariance to symmetries, CENTRIST, GIST, SURF, Spatial pyramid, Local difference binary patterns