  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.

Computer Vision and Pattern Recognition;Databases;Image and Video Processing