OLT: A Toolkit for Object Labeling Applied to Robotic RGB-D Datasets

In this work we present the Object Labeling Toolkit (OLT), a set of software components publicly available for helping in the management and labeling of sequential RGB-D observations collected by a mobile robot. Such a robot can be equipped with an arbitrary number of RGB-D devices, possibly integrating other sensors (e.g. odometry, 2D laser scanners, etc.). OLT first merges the robot observations to generate a 3D reconstruction of the scene from which object segmentation and labeling is conveniently accomplished. The annotated labels are automatically propagated by the toolkit to each RGB-D observation in the collected sequence, providing a dense labeling of both intensity and depth images. The resulting objects’ labels can be exploited for many robotic oriented applications, including high-level decision making, semantic mapping, or contextual object recognition. Software components within OLT are highly customizable and expandable, facilitating the integration of already-developed algorithms. To illustrate the toolkit suitability, we describe its application to robotic RGB-D sequences taken in a home environment.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech. Spanish grant pro- gram FPU-MICINN 2010 and the Spanish projects TAROTH: New developments toward a Robot at Home (DPI2011-25483) and PROMOVE: Advances in mobile robotics for promoting independent life of elders (DPI2014-55826-R