Real-time multiview data fusion for object tracking with RGBD sensors. Issue 8 (1st December 2014)

• Record Type: Journal Article
• Authors: Amamra, Abdenour; Aouf, Nabil
• Is Part Of: Robotica. Volume 34:Issue 8(2016)
• Page Start: 1855
• Page End: 1879
• Publication Date: 2014-12-01
• Subjects: RGBD, -- Real-time, -- Tracking, -- Multiview, -- Kalman filter, -- Robust H∞, -- Covariance intersection, -- GPU; Robots -- Periodicals; 629.89205
• DOI: 10.1017/S026357471400263X
• Languages: English
• ISSNs: 0263-5747

Abstract

SUMMARY: This paper presents a new approach to accurately track a moving vehicle with a multiview setup of red–green–blue depth (RGBD) cameras. We first propose a correction method to eliminate a shift, which occurs in depth sensors when they become worn. This issue could not be otherwise corrected with the ordinary calibration procedure. Next, we present a sensor-wise filtering system to correct for an unknown vehicle motion. A data fusion algorithm is then used to optimally merge the sensor-wise estimated trajectories. We implement most parts of our solution in the graphic processor. Hence, the whole system is able to operate at up to 25 frames per second with a configuration of five cameras. Test results show the accuracy we achieved and the robustness of our solution to overcome uncertainties in the measurements and the modelling.