Skeleton-based Human Action Recognition in Low-Resolution Infrared Images

This paper proposes a recognition method of human action based on human skeleton extraction in low resolution infrared images, which are collected by two thermopile infrared array deployed on the side. Each frame of image is processed sequentially through quantification, interpolation and background removal operations, and the original human skeleton data is then extracted using a thinning algorithm. A standard human skeleton model is established and fitted to acquire the standard human skeleton data. Finally, the continuous human action is divided into several separate actions, and an LSTM network is used for human action recognition. The experimental results have demonstrated that the proposed method can achieve an accurate recognition of human actions.