SkiMap++: Real-Time Mapping and Object Recognition for Robotics

Daniele De Gregorio, Tommaso Cavallari, Luigi Di Stefano; Proceedings of the IEEE International Conference on Computer Vision (ICCV), 2017, pp. 660-668

Abstract


We introduce SkiMap++, an extension to the recently proposed SkiMap mapping framework for robot navigation. The extension deals with enriching the map with semantic information concerning the presence in the environment of certain objects that may be usefully recognized by the robot, e.g. for the sake of grasping them. More precisely, the map can accommodate information about the spatial locations of certain 3D object features, as determined by matching the visual features extracted from the incoming frames through a random forest learned off-line from a set of object models. Thereby, evidence about the presence of object features is gathered from multiple vantage points alongside with the standard geometric mapping task, so to enable recognizing the objects and estimating their 6 DOF poses. As a result, SkiMap++ can reconstruct the geometry of large scale environments as well as localize some relevant objects therein in real-time on CPU.

Related Material


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[bibtex]
@InProceedings{Gregorio_2017_ICCV,
author = {De Gregorio, Daniele and Cavallari, Tommaso and Di Stefano, Luigi},
title = {SkiMap++: Real-Time Mapping and Object Recognition for Robotics},
booktitle = {Proceedings of the IEEE International Conference on Computer Vision (ICCV) Workshops},
month = {Oct},
year = {2017}
}