• Computer Science
  • Published in ArXiv 2019

DetectFusion: Detecting and Segmenting Both Known and Unknown Dynamic Objects in Real-time SLAM

@article{Hachiuma2019DetectFusionDA,
  title={DetectFusion: Detecting and Segmenting Both Known and Unknown Dynamic Objects in Real-time SLAM},
  author={Ryo Hachiuma and Christian Pirchheim and Dieter Schmalstieg and Hideo Saito},
  journal={ArXiv},
  year={2019},
  volume={abs/1907.09127}
}
We present DetectFusion, an RGB-D SLAM system that runs in real-time and can robustly handle semantically known and unknown objects that can move dynamically in the scene. Our system detects, segments and assigns semantic class labels to known objects in the scene, while tracking and reconstructing them even when they move independently in front of the monocular camera. In contrast to related work, we achieve real-time computational performance on semantic instance segmentation with a novel… CONTINUE READING

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