Research Advances in Facial Expression Recognition Technology

Abstract

As a key area in artificial intelligence and computer vision, facial expression analysis technology has been taking hold rapidly, yielding dazzling advances. This technology extracts even the subtlest facial movements to identify when a human is sad, happy, or angry. It has extensive application value in markets like mental diagnosis, secure monitoring, and intelligent interaction. The paper will provide a brief overview of the kernel technology of facial expressions recognition: geometric features, appearance features, and deep learning. And compared the experimental results of different experiments, as a goal, the experiments compare functions of several methods in a multi-dataset context, concentrating the primary problems in the tasks like dataset bias, real-time requirements, and different light levels and partial occlusions in various environments. Eventually, the paper forecasts the imminent growth trend in data fusion and deep learning improvement. This also indicates that emerging technologies, especially in terms of applications, will have the upper hand.