Semantic mapping using object-class segmentation of RGB-D images

@article{Stckler2012SemanticMU,
  title={Semantic mapping using object-class segmentation of RGB-D images},
  author={J{\"o}rg St{\"u}ckler and Nenad Biresev and Sven Behnke},
  journal={2012 IEEE/RSJ International Conference on Intelligent Robots and Systems},
  year={2012},
  pages={3005-3010}
}
For task planning and execution in unstructured environments, a robot needs the ability to recognize and localize relevant objects. When this information is made persistent in a semantic map, it can be used, e. g., to communicate with humans. In this paper, we propose a novel approach to learning such maps. Our approach registers measurements of RGB-D cameras by means of simultaneous localization and mapping. We employ random decision forests to segment object classes in images and exploit… CONTINUE READING
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