WiFi-Based Human Pose Image Generation

This paper tackles a new challenge: how to generate human pose images from wireless signals? Although the optical camera can capture optical images, it is easily restricted by bad lighting. The wireless signals do not rely on visible lights. However, the low-resolution characteristics make previous works can only generate a rough skeleton of human posture, missing a lot of detailed visual information, such as background, appearance, etc. Since the visual information usually maintains unchanged for a period and the wireless signals can capture the movements of the human, in this paper, we propose a framework to generate the target human pose images by combining the wireless signals with an initial optical image. We utilize multiple wireless devices to collect the WiFi signals and a camera to capture the initial optical image. Then a data preprocessing component is designed to preprocess the wireless and vision data. Finally, a deep learning model learns to generate the human pose images from the processed wireless signals and the initial optical image. We conduct experiments to evaluate our proposed framework and results show that it achieves higher accuracy than the state-of-the-art WiFi-based pose estimation method and better visual quality than the state-of-the-art human generation method.