Data Fusion in 3D Vision using a RGB-D Data via Switching Observation Model and Its Application to People Tracking

Kim, D, Vo, B and Vo, B 2013, 'Data Fusion in 3D Vision using a RGB-D Data via Switching Observation Model and Its Application to People Tracking', in 2013 International Conference on Control, Automation and Information Sciences (ICCAIS), Nha Trang, Vietnam, 25-28 November 2013, pp. 91-96.


Document type: Conference Paper
Collection: Conference Papers

Title Data Fusion in 3D Vision using a RGB-D Data via Switching Observation Model and Its Application to People Tracking
Author(s) Kim, D
Vo, B
Vo, B
Year 2013
Conference name 2013 International Conference on Control, Automation and Information Sciences (ICCAIS)
Conference location Nha Trang, Vietnam
Conference dates 25-28 November 2013
Proceedings title 2013 International Conference on Control, Automation and Information Sciences (ICCAIS)
Publisher IEEE
Place of publication United States
Start page 91
End page 96
Total pages 6
Abstract In this paper, we propose a new method for 3D people tracking with RGB-D observations. The proposed method fuses RGB and depth data via a switching observation model. Specifically, the proposed switching observation model intelligently exploits both final detection results and raw signal intensity in a complementary manner in order to cope with missing detections. In real-world applications, the detector response to RGB data is frequently missing. When this occurs the proposed algorithm exploits the raw depth signal intensity. The fusion of detection result and raw signal intensity is integrated with the tracking task in a principled manner via the Bayesian paradigm and labeled random finite set (RFS). Our case study shows that the proposed method can reliably track people in a recently published 3D indoor data set.
Subjects Computer Vision
DOI - identifier 10.1109/ICCAIS.2013.6720536
Copyright notice © 2013 Crown
ISBN 9781479905720
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