Eurekalert July 5, 2018
Researchers in Russia used the theory of fuzzy sets and probability theory to develop a video recognition algorithm. The algorithm significantly improves the accuracy (by 2-6% compared to earlier experiments) of identifying faces by video in real time with a small number of images for several well-known neural network architectures, such as VGGFace, VGGFace2, ResFace and LightCNN. It estimates to what degree one frame is closer to one person, and to what degree the other frame is closer to the next person. Then it compares how similar the training still photos of these two people are to each other. It then adds the third person to the mix and evaluates to whom they are more similar – the first or second. It then corrects recognition errors… read more. TECHNICAL ARTICLEÂ 1 , 2