The Quick, Draw! Dataset is a Google dataset with a collection of
50 million drawings, divided in 345 categories, collected from the users
of the game Quick, Draw!. In contrast with most of the existing image
datasets, in the Quick, Draw! Dataset, drawings are stored as time
series of pencil positions instead of a bitmap matrix composed by
pixels. This aspect makes this dataset the largest doodle dataset
available at the time. The Quick, Draw! Dataset is presented as a great
opportunity to researchers for developing and studying machine learning
techniques. Due to the size of this dataset and the nature of its
source, there is a scarce of information about the quality of the
drawings contained. In this paper a statistical analysis of three of the
classes contained in the Quick, Draw! Dataset is depicted: mountain,
book and whale. The goal is to give to the reader a first impression of
the data collected in this dataset. For the analysis of the quality of
the drawings a Classification Neural Network was trained to obtain a
classification score. Using this classification score and the parameters
provided by the dataset, a statistical analysis of the quality and
nature of the drawings contained in this dataset is provided.
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