AlgoFace, a B2B & B2G Ethical Face AI Enablement Engine that leverages edge AI to create private, accurate, and ethical applied AI solutions, announced that it has been granted a second patent by the US Patent Office for the company’s new Facial Image Retrieval System technology. This patent unlocks the potential to measure and score the similarities between textual queries regarding the face with the associated facial image characteristics in photos and videos. The newly issued patent complements AlgoFace’s previously issued patent which focuses on the initial extracting of detailed facial attributes from facial images thereby enabling database searches using precise textual descriptions.
In July of 2021, AlgoFace was granted a patent for a Computer Vision Neural Network System, which uses computer vision based deep learning to extract up to 20 different facial attributes from a single face without identification of the individual. The new patent uses natural language processing to extract the same facial attributes using textual descriptions. The two patents combined represent a breakthrough and huge potential for detailed contextual facial image indexing and retrieval.
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“Our patented technology now allows users to search databases in real time using contextual search which greatly reduces the time to find images. It has many positive use cases in identifying facial images and characteristics without ever uniquely identifying the individual,” stated Taleb Alashkar, AlgoFace’s Chief Technology Officer.
“The two patents combined are a game changer in how current facial image searches are performed and offer numerous opportunities, particularly as they relate to corporate innovation efforts,” mentioned Andrew J. Bart, CEO of AlgoFace.
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