Real-time multiview data fusion for object tracking with RGBD sensors

• URL: http://arxiv.org/abs/2110.15815v1
• Date: Thu, 28 Oct 2021 09:24:49 GMT
• Title: Real-time multiview data fusion for object tracking with RGBD sensors
• 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. Next, we present a sensor-wise filtering system to correct for an unknown vehicle motion.
• Score: 4.68299658663016
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: 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.

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