@INPROCEEDINGS{8324393, 
author={Y. Sun and M. Liu and M. Q. H. Meng}, 
booktitle={2017 IEEE International Conference on Robotics and Biomimetics (ROBIO)}, 
title={Invisibility: A moving-object removal approach for dynamic scene modelling using RGB-D camera}, 
year={2017}, 
volume={}, 
number={}, 
pages={50-55}, 
abstract={Scene modelling is of great importance for robots in unknown environments. Existing Visual Simultaneous Localization and Mapping (Visual SLAM) approaches are able to build impressive scene models using RGB-D cameras in static scenes. In dynamic scenes, however, moving objects can be recorded as spurious objects, which contaminates the resulting scene models. In order to build clear scene models, we propose a novel moving-object removal approach for scene modelling algorithms in this paper. Our approach does not rely on prior knowledge, such as appearance features or initial segmentation. In addition, the proposed approach does not require an initialization process, which is different from most background subtraction algorithms. The experimental results demonstrate that our approach is able to effectively remove moving objects and assist scene modelling algorithms to build clear models in dynamic scenes.}, 
keywords={SLAM (robots);cameras;image motion analysis;object detection;RGB-D camera;Visual SLAM;Visual Simultaneous Localization and Mapping approaches;clear scene models;dynamic scene modelling;dynamic scenes;impressive scene models;moving objects;novel moving-object removal approach;scene modelling algorithms;spurious objects;static scenes;Cameras;Heuristic algorithms;Image segmentation;Integrated optics;Legged locomotion;Motion segmentation;Optical imaging}, 
doi={10.1109/ROBIO.2017.8324393}, 
ISSN={}, 
month={Dec},}