Digital Signal and Image Processing: University of Genoa (90520) - Fall 2019 - Final project
Live Notebook on Colab
Abstract
Kalman filter, Kalman smoothing and Extended Kalman filter algorithms are briefly presented. An application of Kalman filtering and smoothing procedures is proposed to estimate the trajectories of tennis ball. In the provided IPtython notebook the Kalman filter implementation has been revisited with respect to the version proposed during lab activities, while the Kalman smoothing algorithm has been implemented from scratch. Real data coming from a private tennis club instrumented with a 3D stereoscopic system were used. Given an extremely simple physics linear model and sufficient accuracy of measurements, the Kalman smoothing solution was shown to be a trivial yet effective strategy to deal with relatively small temporal holes due to missing frames.