Open Access
An efficient motion segmentation algorithm for multibody RGB-D slam
Youbing Wang,Shoudong Huang +1 more
- 01 Jan 2013
3
TL;DR: A simple motion segmentation algorithm using only two frames of RGB-D data is proposed, and both simulational and experimental segmentation results show its efficiency and reliability.
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Abstract: A simple motion segmentation algorithm using only two frames of RGB-D data is proposed, and both simulational and experimental segmentation results show its efficiency and reliability. To further verify its usability in multibody SLAM scenarios, we firstly apply it to a simualted typical multibody SLAM problem with only a RGB-D camera, and then utilize it to segment a real RGB-D dataset collected by ourselves. Based on the good results of our motion segmentation algorithm, we can get satisfactory SLAM results for the simualted problem and the segmenation results using real data also enable us to get visual odometry for each motion group thus facilitate the following steps to solve the practical multibody RGB-D SLAM problems.
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Citations
Towards dense moving object segmentation based robust dense RGB-D SLAM in dynamic scenarios
Youbing Wang,Shoudong Huang +1 more
- 01 Jan 2014
TL;DR: This work proposes to combine dense moving object segmentation with dense SLAM to enhance its robustness in dynamic scenarios and proposes some effective measures to improve upon them so that better results can be achieved.
Motion segmentation based robust RGB-D SLAM
Youbing Wang,Shoudong Huang +1 more
- 01 Jun 2014
TL;DR: A sparse feature-based motion segmentation algorithm for RGB-D data is proposed which offers a unified way to handle outliers and dynamic scenarios and is efficient and effective in handling general static andynamic scenarios.
Fast segmentation of sparse 3D point trajectories using group theoretical invariants
Vasileios Zografos,Reiner Lenz,Erik Ringaby,Michael Felsberg,Klas Nordberg +4 more
- 01 Nov 2014
TL;DR: A novel approach to segmenting different motions from 3D trajectories using the theory of transformation groups to derive a set of invariants of 3D points located on the same rigid object that is robust to perspective distortions and degenerate configurations.
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