Runz, M;
Buffier, M;
Agapito, L;
(2019)
MaskFusion: Real-Time Recognition, Tracking and Reconstruction of Multiple Moving Objects.
In: Chu, D and Gabbard, JL and Grubert, J and Regenbrecht, H, (eds.)
(Proceedings) 17th IEEE International Symposium on Mixed and Augmented Reality (ISMAR).
(pp. pp. 10-20).
IEEE: Munich, Germany.
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Abstract
We present MaskFusion, a real-time, object-aware, semantic and dynamic RGB-D SLAM system that goes beyond traditional systems which output a purely geometric map of a static scene. MaskFusion recognizes, segments and assigns semantic class labels to different objects in the scene, while tracking and reconstructing them even when they move independently from the camera. As an RGB-D camera scans a cluttered scene, image-based instance-level semantic segmentation creates semantic object masks that enable realtime object recognition and the creation of an object-level representation for the world map. Unlike previous recognition-based SLAM systems, MaskFusion does not require known models of the objects it can recognize, and can deal with multiple independent motions. MaskFusion takes full advantage of using instance-level semantic segmentation to enable semantic labels to be fused into an object-aware map, unlike recent semantics enabled SLAM systems that perform voxel-level semantic segmentation. We show augmented-reality applications that demonstrate the unique features of the map output by MaskFusion: instance-aware, semantic and dynamic. Code will be made available.
| Type: | Proceedings paper |
|---|---|
| Title: | MaskFusion: Real-Time Recognition, Tracking and Reconstruction of Multiple Moving Objects |
| Event: | 17th IEEE International Symposium on Mixed and Augmented Reality (ISMAR) |
| Location: | Munich, GERMANY |
| Dates: | 16 October 2018 - 20 October 2018 |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1109/ISMAR.2018.00024 |
| Publisher version: | https://doi.org/10.1109/ISMAR.2018.00024 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| Keywords: | Visual SLAM, SLAM, Visualization, Tracking, Mapping, Fusion, RGBD, Multi-object Recognition, Context, Semantic, Detection Real-time, Augmented-Reality, Robotics, 3D, SEGMENTATION, LOCALIZATION |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10074870 |
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