With the rapid development of artificial intelligence in the field of computer vision,more and more classical artificial intelligence algorithms are applied to multiple face recognition research.Among them,the MTCNN algorithm performs well in multi-face recognition,but there is still a relatively large space for improvement in recognition accuracy.In this study,based on the classical MTCNN algorithm framework,the refinement of its sub-algorithm NMS algorithm was evaluated and improved.The performance differences between the NMS algorithm and the improved NMS algorithm were compared and theoretically analyzed in each cascade network of P-Net,R-Net,and O-Net.The improved algorithm was evaluated and identified in multiple ways combining subjective and objective and horizontal comparison and longitudinal comparison.The results showed that the model designed in this paper achieves a face recognition accuracy of 94.56%on the LFW dataset.It can provide a reference for multi-face recognition.
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