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Fiducial markers are used in a broad spectrum of applications to tag objects visually and estimate their pose using a camera sensor. Their flexibility, simplicity, and cost-effectiveness make them relevant in research setups and experiments. While the detection and pose estimation frequency are related to the computation capability of the used machine; high frame-rate cameras and high-resolution cameras are shown to harden the recognition rate. To this aim, we provide a dynamic region-of-interest(ROI) based filter for the inputted images in order to decrease the computational load to cope with high throughput systems. To do so, we leverage the kinematic properties of the objects tagged with the fiducial marker and use an Unscented Kalman Filter (UKF) to update its state.
Stefano Mutti,Giovanni Dimauro, andNicola Pedrocchi
"Kinematic-aware UKF-based fast fiducial marker tracker", Proc. SPIE 12621, Multimodal Sensing and Artificial Intelligence: Technologies and Applications III, 1262115 (9 August 2023); https://doi.org/10.1117/12.2674144
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Stefano Mutti, Giovanni Dimauro, Nicola Pedrocchi, "Kinematic-aware UKF-based fast fiducial marker tracker," Proc. SPIE 12621, Multimodal Sensing and Artificial Intelligence: Technologies and Applications III, 1262115 (9 August 2023); https://doi.org/10.1117/12.2674144