  A lot of research has been devoted to identity documents analysis and
recognition on mobile devices. However, no publicly available datasets designed
for this particular problem currently exist. There are a few datasets which are
useful for associated subtasks but in order to facilitate a more comprehensive
scientific and technical approach to identity document recognition more
specialized datasets are required. In this paper we present a Mobile Identity
Document Video dataset (MIDV-500) consisting of 500 video clips for 50
different identity document types with ground truth which allows to perform
research in a wide scope of document analysis problems. The paper presents
characteristics of the dataset and evaluation results for existing methods of
face detection, text line recognition, and document fields data extraction.
Since an important feature of identity documents is their sensitiveness as they
contain personal data, all source document images used in MIDV-500 are either
in public domain or distributed under public copyright licenses.
  The main goal of this paper is to present a dataset. However, in addition and
as a baseline, we present evaluation results for existing methods for face
detection, text line recognition, and document data extraction, using the
presented dataset.
  (The dataset is available for download at ftp://smartengines.com/midv-500/.)
