Disclosed are a self-driving-oriented human-machine collaborative perception method and system. The method comprises: capturing head images of a driver by means of using binocular infrared CCDs arranged at different positions in a vehicle, extracting facial features and obtaining feature corner points; establishing a mapping relationship between the three-dimensional line of sight of the driver and pixels on environmental perception camera imaging, obtaining a gazing point of the driver, and saving the gazing point to a fixation point cache database; on the basis of the fixation point cache database, performing eye movement analysis on fixation target frequency and fixation duration to obtain eye movement states, constructing an extended dimension environment perception image database, and adjusting distribution weights of image processing neural networks during the process of self driving. The present invention rapidly positions a region of interest in an image in an intelligent camera by means of visual tracking and a human eye attention mechanism, and accelerates the processing speed of environmental perception system information by using perception fusion technologies, which can significantly reduce hardware operation requirements of the perception system and improve the real-time performance of the system, and is thus economical.
SELF-DRIVING-ORIENTED HUMAN-MACHINE COLLABORATIVE PERCEPTION METHOD AND SYSTEM