Indoor scene recognition through object detection

Abstract— Scene recognition is a highly valuable perceptual ability for an indoor mobile robot, however, current approaches for scene recognition present a significant drop in performance for the case of indoor scenes. We believe that this can be explained by the high appearance variability of indoor environments. This stresses the need to include highlevel semantic information in the recognition process. In this work we propose a new approach for indoor scene recognition based on a generative probabilistic hierarchical model that uses common objects as an intermediate semantic representation. Under this model, we use object classifiers to associate lowlevel visual features to objects, and at the same time, we use contextual relations to associate objects to scenes. As a further contribution, we improve the performance of current state-ofthe-art category-level object classifiers by including geometrical information obtained from a 3D range sensor that facilitates the implementatio...

• Type: Journal
• Year: 2010
• Where: ICRA
• Authors: Pablo Espinace, Thomas Kollar, Alvaro Soto, Nicholas Roy
• Keywords: ICRA 2010, Indoor Scene, Indoor Scene Recognition, Robotics, Scene Recognition