continually optimizing state-of-the-art face recognition methods
Research at Cognitec, as well as our contributions to international research projects, involve the following subjects:
- deep learning techniques
- facial image forgeries and manipulations
- face recognition with low-resolution images and video material
- facial images with substantial pose variations and occlusions
- tracking people in crowds, even when the face is not visible
Facial image forgeries and manipulations
Recent years have seen significant advances in face forgery and manipulation methods that make it possible to create genuine-looking images and videos with modified facial identities. Deepfakes in particular—the exchange of a face in an image or a video with the face of a different person—have become known to a wider public due to media coverage on high-profile cases.
Read about measures to prevent facial image forgeries entering biometric systems in our white paper.
Cognitec is meeting the global demand for face recognition technologies that work well for masked faces by continuously improving our algorithms and increasing the matching accuracy for partially occluded faces.
Research and development in the past two years have resulted in robust algorithms for detecting and matching faces partly covered by protective masks. Evidently, matching accuracy differs in comparison to unmasked faces, since masks occlude a large area of the face and remove substantial information needed for comparison tasks.
Therefore, unmasked faces will remain the gold standard for automated face recognition technologies. High-security applications that need to establish a person's identity, like 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.
Some face recognition companies are publishing doubtful claims about their technologies reaching the same matching accuracy for faces covered by masks. For accurate performance data, pleasesee the latest NIST test results on mask effects.
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.
Technical University Dresden
Cognitec supports research projects at the Institute of Mathematics at the TU Dresden that study support vector machines and numerical optimization.
Cognitec has been contributing to the iMARS research project since September 2020. Funded by the European Commission for 48 months, the project examines the use of counterfeit travel documents for crossing borders, which has increased the risk of not identifying known criminals, terrorists, or previously unknown subjects such as victims of human trafficking. Document fraud has established itself as organized crime in the European Union and constitutes significant financial consequences for member states. iMARS develops solutions to better detect document fraud and image manipulation forgeries in the ID document life cycle, from issuance to verification and forensic investigation. More information.
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. More information.