Performance Analysis in Artificial Intelligence Facial Recognition Based on Machine Vision Algorithms

This article explores the performance of artificial intelligence facial recognition technology based on machine vision algorithms. With the rapid development of artificial intelligence technology, facial recognition, as an important application in the field of machine vision, can be applied in areas such as identity verification and public safety. We conducted an in-depth analysis of the performance differences between traditional feature extraction methods and deep learning models in facial recognition, and verified the advantages of deep learning models in handling large-scale datasets and complex scenes through experiments. Explored the influence of factors such as lighting, posture, and occlusion on recognition performance, and proposed strategies such as data augmentation and model optimization to improve recognition accuracy. The research results of this article provide valuable references for the further development and application of facial recognition technology based on machine vision algorithms.