Trajectory tracking in a wide field using two fixed cameras and neural network
Abstract
A low-cost method consisting of two fixed cameras was utilized to demonstrate a way of tracking objects in a wide field. The cameras were placed and positioned in an angle where there exist overlapping views such that the tracking of a moving object continues as it disappears from the view of one of the cameras. With the dimensions of the field known, pre- determined points from the image can be used to train a neural network that can then automatically convert a player’s position in image coordinates to actual world coordinates.
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