Motion Removal from Moving Platforms: An RGB-D Data-based Motion Detection, Tracking and Segmentation Approach

Yuxiang Sun; Ming Liu; Max Q.-H. Meng

doi:10.1109/ROBIO.2015.7418963

Motion Removal from Moving Platforms: An RGB-D Data-based Motion Detection, Tracking and Segmentation Approach

Yuxiang Sun
, Ming Liu
, Max Q.-H. Meng

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

5 Citations (Scopus)

Abstract

Moving objects are the primary concern for most robot vision applications in dynamic environments. The existence of moving objects can lead to ambiguous decisions such as searching loop closure in visual mapping applications. Eliminating moving objects from the image sequences captured by moving camera is the key challenge. In this paper, a novel approach for moving objects removal using a hand-held RGB-D camera is proposed. Only the visual and depth data are used. No other sensor or prior information is needed in this paper. Our approach can be exploited as a pre-processing stage to filter out data that are associated with moving objects. We test our approach with various ego-motion patterns in different environments. The experimental results demonstrate that our approach can provide a practical solution for motion removal from moving platforms using an RGB-D camera.

Original language	English
Title of host publication	Proceedings of the 2015 IEEE Conference on Robotics and Biomimetics
Publisher	IEEE
Pages	1377-1382
ISBN (Electronic)	978-1-4673-9675-2
DOIs	https://doi.org/10.1109/ROBIO.2015.7418963
Publication status	Published - Dec 2015
Event	2015 IEEE International Conference on Robotics and Biomimetics (IEEE-ROBIO 2015) - Zhuhai, China Duration: 6 Dec 2015 → 9 Dec 2015 https://ieeexplore.ieee.org/xpl/conhome/7397291/proceeding

Conference

Conference	2015 IEEE International Conference on Robotics and Biomimetics (IEEE-ROBIO 2015)
Place	China
City	Zhuhai
Period	6/12/15 → 9/12/15
Internet address	https://ieeexplore.ieee.org/xpl/conhome/7397291/proceeding

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@inproceedings{6a167aebe6fe4654a1c344e4e0f5387f,

title = "Motion Removal from Moving Platforms: An RGB-D Data-based Motion Detection, Tracking and Segmentation Approach",

abstract = "Moving objects are the primary concern for most robot vision applications in dynamic environments. The existence of moving objects can lead to ambiguous decisions such as searching loop closure in visual mapping applications. Eliminating moving objects from the image sequences captured by moving camera is the key challenge. In this paper, a novel approach for moving objects removal using a hand-held RGB-D camera is proposed. Only the visual and depth data are used. No other sensor or prior information is needed in this paper. Our approach can be exploited as a pre-processing stage to filter out data that are associated with moving objects. We test our approach with various ego-motion patterns in different environments. The experimental results demonstrate that our approach can provide a practical solution for motion removal from moving platforms using an RGB-D camera.",

author = "Yuxiang Sun and Ming Liu and Meng, \{Max Q.-H.\}",

year = "2015",

month = dec,

doi = "10.1109/ROBIO.2015.7418963",

language = "English",

pages = "1377--1382",

booktitle = "Proceedings of the 2015 IEEE Conference on Robotics and Biomimetics",

publisher = "IEEE",

address = "United States",

note = "2015 IEEE International Conference on Robotics and Biomimetics (IEEE-ROBIO 2015) ; Conference date: 06-12-2015 Through 09-12-2015",

url = "https://ieeexplore.ieee.org/xpl/conhome/7397291/proceeding",

}

Sun, Y, Liu, M & Meng, MQ-H 2015, Motion Removal from Moving Platforms: An RGB-D Data-based Motion Detection, Tracking and Segmentation Approach. in Proceedings of the 2015 IEEE Conference on Robotics and Biomimetics., 7418963, IEEE, pp. 1377-1382, 2015 IEEE International Conference on Robotics and Biomimetics (IEEE-ROBIO 2015), Zhuhai, China, 6/12/15. https://doi.org/10.1109/ROBIO.2015.7418963

Motion Removal from Moving Platforms: An RGB-D Data-based Motion Detection, Tracking and Segmentation Approach. / Sun, Yuxiang; Liu, Ming; Meng, Max Q.-H.
Proceedings of the 2015 IEEE Conference on Robotics and Biomimetics. IEEE, 2015. p. 1377-1382 7418963.

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

TY - GEN

T1 - Motion Removal from Moving Platforms

T2 - 2015 IEEE International Conference on Robotics and Biomimetics (IEEE-ROBIO 2015)

AU - Sun, Yuxiang

AU - Liu, Ming

AU - Meng, Max Q.-H.

PY - 2015/12

Y1 - 2015/12

N2 - Moving objects are the primary concern for most robot vision applications in dynamic environments. The existence of moving objects can lead to ambiguous decisions such as searching loop closure in visual mapping applications. Eliminating moving objects from the image sequences captured by moving camera is the key challenge. In this paper, a novel approach for moving objects removal using a hand-held RGB-D camera is proposed. Only the visual and depth data are used. No other sensor or prior information is needed in this paper. Our approach can be exploited as a pre-processing stage to filter out data that are associated with moving objects. We test our approach with various ego-motion patterns in different environments. The experimental results demonstrate that our approach can provide a practical solution for motion removal from moving platforms using an RGB-D camera.

AB - Moving objects are the primary concern for most robot vision applications in dynamic environments. The existence of moving objects can lead to ambiguous decisions such as searching loop closure in visual mapping applications. Eliminating moving objects from the image sequences captured by moving camera is the key challenge. In this paper, a novel approach for moving objects removal using a hand-held RGB-D camera is proposed. Only the visual and depth data are used. No other sensor or prior information is needed in this paper. Our approach can be exploited as a pre-processing stage to filter out data that are associated with moving objects. We test our approach with various ego-motion patterns in different environments. The experimental results demonstrate that our approach can provide a practical solution for motion removal from moving platforms using an RGB-D camera.

UR - https://www.scopus.com/pages/publications/84964454420

UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-84964454420&origin=recordpage

U2 - 10.1109/ROBIO.2015.7418963

DO - 10.1109/ROBIO.2015.7418963

M3 - RGC 32 - Refereed conference paper (with host publication)

SP - 1377

EP - 1382

BT - Proceedings of the 2015 IEEE Conference on Robotics and Biomimetics

PB - IEEE

Y2 - 6 December 2015 through 9 December 2015

ER -

Motion Removal from Moving Platforms: An RGB-D Data-based Motion Detection, Tracking and Segmentation Approach

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