Optical Fiber Intelligent Carpet for Gait Recognition With a Local Strain and Global Contour Dual-Modality Attention Network

Gait recognition is an important technology to perceive human motion patterns, which is widely used in intelligent medical, security monitoring and human-computer interaction. Traditional gait recognition methods mostly rely on image analysis or wearable sensors, which are restricted by environmental conditions and difficult to balance accuracy and convenience. This paper constructs an intelligent carpet gait recognition system using Optical Frequency Domain Reflectometry (OFDR) based distributed fiber optic sensing. By embedding two-dimensional optical fiber array inside the carpet, it achieves high-density perception of strains of the foot. A local strain and global contour dual-modality attention network is proposed for gait recognition. Firstly, a strain graph attention network is designed to process the original strain data, which can construct the dynamic correlation between fibers and extract key fiber strain features. Then, the strain signal is transformed into image and a pressure gradient guided non-local attention module is introduced to focus on the contact area and contour of the sole, so as to enhance the global spatial features of the gait. Finally, the dual-modality features are fused to realize gait recognition. The proposed method is tested on 16 kinds of gaits. The quantitative and qualitative experiment results show that the proposed method can effectively collect gait data and has excellent recognition accuracy.