Multimodal Human Pose Estimation: A Wi-Fi-Driven Approach With Adaptive Kernel Selection

HPE-Li++ is a new system that estimates human pose (the position and angles of body parts) using both Wi-Fi signals and camera data together, rather than relying only on camera images. The system uses a specialized neural network (a type of AI model) with adaptive kernel selection (a technique that automatically adjusts how the AI processes different parts of the input) to achieve accurate 3D skeletal pose detection while using very little computing power, making it practical for devices with limited resources.