  In RoboCup SPL, soccer field segmentation has been widely recognised as one
of the most critical robot vision problems. Key challenges include dynamic
light condition, different calibration status for individual robot, various
camera prospective and more. In this paper, we propose a dataset that contains
20 videos recorded with Nao V5/V6 humanroid robots by team rUNSWift under
different circumstances. Each of the videos contains several consecutive high
resolution frames and the corresponding labels for field. We propose this
dataset to provide training data for the league to overcome field segmentation
problem. The dataset will be available online for download. Details of
annotation and example of usage will be explained in later sections.
