continually optimizing state-of-the-art face recognition methods

Internal research and participation in international research projects involve the following subjects:

  • deep learning techniques
  • identification from photographs or video data using 3D facial images
  • face recognition with low-resolution images and video material
  • pose variation and partial occlusion in facial images
  • tracking people in crowds, even when the face is not visible

Masked faces

In light of recent global developments, researchers at Cognitec have investigated the impact of face masks on face recognition accuracy, especially for unsupervised scenarios, where many faces are being matched against large databases. As expected, our current technology matches masked faces, but tests showed an overall decrease of face detection rates and an increase of false match rates, in comparison to unmasked faces.

Since masks occlude a large area of the face, removing substantial information needed for comparison tasks, matching accuracy will evidently decrease. Therefore, unmasked faces will remain the gold standard for automated face recognition technologies. Some face recognition companies are publishing doubtful claims about their technologies reaching the same matching accuracy for faces covered by masks.

High-security applications that need to establish a person's identity, for example, border control or passport issuance, will most likely require the removal of masks. But as long as wearing masks is required or common in everyday life, recognizing masked faces is becoming an expected feature for systems that unlock phones, track and count people, measure demographics, or identify persons of interest.

Cognitec is responding to such market demands as we continuously improve our algorithms. Our research and development team constantly works on increasing the accuracy for partially occluded faces. In addition, we are using training data with masked faces, and current lab results already show significant advances for detecting and matching faces with masks. Upcoming releases of our products will soon provide this capability to our customers.

Conference sponsorships

Cognitec regularly sponsors international biometrics research conferences:

  • IEEE Sixth International Conference on Biometrics: Theory, Applications and Systems
  • International Conference on Biometrics

Working with universities

University of Applied Sciences (Hochschule für Technik und Wirtschaft) Dresden

Since 2010, Cognitec has been working with the department of artificial intelligence at HTW Dresden on the development of intelligent service assistance systems/humanoid robots that will react naturally and intuitively to the human user. Face recognition can lend robots a multitude of capabilities: detecting faces, estimating a person's gender and age, following faces in space and sensing moods.

University of Surrey

Cognitec is working with the University of Surrey on face models and improved face recognition for facial information extracted from multiple frames in video sequences. This involves fitting a 2D or 3D morphable face model to input face images, without restriction to the subject’s pose.

Technical University Dresden

Cognitec supports research projects at the Institute of Mathematics at the TU Dresden that study support vector machines and numerical optimization.

International research projects


ABC4EU stands for Automated Border Control Gates for Europe. It is an EU wide project and involves a Consortium of 15 partners from 8 different countries, with a budget of 16,8 Million Euros, 70% EU funding. The aim is to make border control more flexible by enhancing the workflow and harmonizing the functionalities of Automated Border Control (ABC) gates, which are only one example of automation. Project started in January 2014 and will last for 3,5 years. The project is led by Indra Sistemas S.A. from Spain.

Project website


In the framework of the EmAsIn project, seven scientific and industrial partners recently joined forces to develop a new assistance system for people suffering from affective disorders or dementia. The assistance system is intended to receive a high degree of personalization, recognize habitual human communication patterns, deduce emotional and mental states from these patterns, and ultimately evolve from a technical tool into a competent assistant thanks to innovative interaction concepts.

Project website (in German)


The project aims to gain new insights about how assistance robots can be employed in the care of the elderly. Possible tasks carried out by such robots include night watch, helping with executing cognitive and motoric exercises, and providing support for therapists and carers. The two-year project started in April 2017 and is funded by the Free State of Saxony and by the European Union through EFRE (Europäischer Fonds für regionale Entwicklung; English: European Fund for Regional Development) with more than 800.000 Euro. Cognitec intends to contribute to the project with improvements of the existing face analysis technologies, both for person identification and for the estimation of person characteristics such as age and gender, taking into account the specific operating conditions of the assistance robots.