  In many computer vision domains, the input images must conform with the
pinhole camera model, where straight lines in the real world are projected as
straight lines in the image. Performing computer vision tasks on live sports
broadcast footage imposes challenging requirements where the algorithms cannot
rely on a specific calibration pattern must be able to cope with unknown and
uncalibrated cameras, radial distortion originating from complex television
lenses, few visual clues to compensate distortion by, and the necessity for
real-time performance. We present a novel method for single-image automatic
lens distortion compensation based on deep convolutional neural networks,
capable of real-time performance and accuracy using two highest-order
coefficients of the polynomial distortion model operating in the application
domain of sports broadcast. Keywords: Deep Convolutional Neural Network, Radial
Distortion, Single Image Rectification
