A method and a system for acquiring a line-of-sight direction of human eyes by means of a single camera. Said method comprises: step S1, using an image data acquisition device to acquire facial images at various angles, the facial images being used as data for neural network deep learning training; step S2, at least calculating the coordinates of the position of human eyes in the images acquired in step S1 and the coordinates of the position of corresponding line-of-sight gaze; step S3, inputting, into a neural network for performing machine learning, the facial images at the various angles in step S1 comprising the coordinates of the position of the human eyes and the line-of-sight gaze, and performing training to obtain a neural network capable of correctly outputting the line-of-sight direction when a facial image is inputted; step S4, acquiring, by means of a real-time acquisition camera, a facial image of a driver while driving, inputting same into the trained neural network, and the neural network outputting the real-time line-of-sight direction corresponding to the facial image. The method uses an improved image data training method, a coordinate system transformation method, and a neural network model adapted thereto; the accuracy of the line-of-sight direction of human eyes calculated by the network model is high, satisfying the needs of various autonomous driving/assisted driving.
METHOD AND SYSTEM FOR ACQUIRING LINE-OF-SIGHT DIRECTION OF HUMAN EYES BY MEANS OF SINGLE CAMERA