Our student Axel Baldanza uploaded a new preprint: “Piecewise linear prediction model for action tracking in sports“.
Abstract: “Recent tracking methods in professional team sports
reach very high accuracy by tracking the ball and players.
However, it remains difficult for these methods to perform
accurate real-time tracking in amateur acquisition conditions
where the vertical position or orientation of the camera is not
controlled and cameras use heterogeneous sensors. This article
presents a method for tracking interesting content in an amateur
sport game by analyzing player displacements. Defining optical
flow of the foreground in the image as the player motions,
we propose a piecewise linear supervised learning model for
predicting the camera global motion needed to follow the action.”