ClientScan is the leading high-performance real-time face detection AI application, providing facial recognition and age range estimation.   ClientScan is a complete “ground up” development of a Convolutional Neural Network (CNN) application, designed to achieve world-class recognition accuracy on low-cost platforms such as Linux systems and Microsoft Windows PCs, and is based on academic research from the Visual Geometry Group at Oxford University.
ClientScan takes face detection to the next level.  Our non-intrusive face detection provides the highest level of security and our advanced application supports multi-site installations.  ClientScan is architected to be secure, scalable, performant, easy to use, and install across a number of sectors. The solution architecture ensures ClientScan is well suited to solve the challenge of Self-Exclusion within the land-based gaming sector, ensuring compliance with recognising and protecting self-excluded gamblers. 
ClientScan achieves high levels of performance and accuracy through the use of advanced techniques developed at the University of Oxford.  ClientScan, performs a non-intrusive face detection in real-time from existing video feeds, a geometric and image normalisation is then performed on each detected face. A deep neural network then runs on the normalised face to extract ‘face features’.  This information is used to classify the faces of different people and is robust to variations in lighting and pose.  Extracted features from the real-time feed are then matched for age estimation and against faces in, for example, the ‘Self Excluded’ subject database. When a high probability match is found the name of the subject is presented to the system user and alerts are sent to notify staff in real time. Faces of people who have not chosen to be on the ’Self Excluded’ list are ignored by ClientScan, ensuring compliance with GDPR. Our anonymous age range estimation assists staff with entry to age-restricted venues.

ClientScan

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