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A lot of research has been devoted to identity documents analysis andrecognition on mobile devices. However, no publicly available datasets designedfor this particular problem currently exist. There are a few datasets which areuseful for associated subtasks but in order to facilitate a more comprehensivescientific and technical approach to identity document recognition morespecialized datasets are required. In this paper we present a Mobile IdentityDocument Video dataset (MIDV-500) consisting of 500 video clips for 50different identity document types with ground truth which allows to performresearch in a wide scope of document analysis problems. The paper presentscharacteristics of the dataset and evaluation results for existing methods offace detection, text line recognition, and document fields data extraction.Since an important feature of identity documents is their sensitiveness as theycontain personal data, all source document images used in MIDV-500 are eitherin public domain or distributed under public copyright licenses.  The main goal of this paper is to present a dataset. However, in addition andas a baseline, we present evaluation results for existing methods for facedetection, text line recognition, and document data extraction, using thepresented dataset.  (The dataset is available for download at ftp://smartengines.com/midv-500/.)

MIDV-500: A Dataset for Identity Documents Analysis and Recognition on Mobile Devices in Video Stream