Abstract: Disclosed is a method and system for predicting a touch interaction position on a large display based on a binocular camera. The method includes: separately acquiring arm movement video frames of a user and facial and eye movement video frames of the user by a binocular camera; extracting a video clip of each tapping action from the arm movement video frames and the facial and eye movement video frames and obtaining a key frame by screening; marking the key frame of each tapping action with coordinates to indicate coordinates of a finger in a display screen; inputting the marked key frame to an efficient convolutional network for online video understanding (ECO)-Lite neural network for training to obtain a predictive network model; and inputting a video frame of a current operation to be predicted to the predictive network model and outputting a touch interaction position predicted for the current operation.

Abstract: This application discloses a wearable member. The wearable member includes a main body, a gas emitter, and a light source, where the main body includes a first body and a second body; the first body and the second body jointly define a target region; the gas emitter and the light source are disposed in the main body; the gas emitter emits gas to the target region; the light source emits a light beam to the target region; and an overlapped region between a region including the gas and a region including the light beam is used to display an image.