Adaptive Eye Tracking Methods

Abstract

The invention provides a self-adaptive eye movement tracking method. The method comprises the following steps: S1, collecting a frontal facial image of a testee by an eye movement camera, and inputting the same into a controller; S2, processing the facial image by the controller, controlling an electric bracket to move according to a position of the facial image to adjust a position of the eye movement camera; S3, aligning infrared light emitters with the testee, controlling the infrared light emitters to work, and continuing to collect an eye image of the testee by the eye movement camera; and S4, processing the eye image of the testee by the controller, and acquiring approaching coordinates of a human eye movement gaze point according to the eye image. Posture of an eye movement data collector can be automatically adjusted in a process of eye movement data tracking according to posture of the testee, thus it is ensured that the facial image of the testee is always in a collection range of the eye movement data collector, the frontal facial image of the testee can be tracked in time even if the posture of the testee is changed, efficiency is high, and precision of final eye movement data acquisition is guaranteed.

Description

technical field [0001] The present invention relates to the field of eye movement tracking, in particular to an adaptive eye movement tracking method. Background technique [0002] Eye tracking is a technology that uses mechanical, electronic, optical and other detection methods to obtain data information such as the spatial position of the eyeball, the direction of eye gaze, and pupil parameters of the subject. This technology is widely used in psychology, ergonomics, industrial design, advertising design, eye control and human-computer interaction, virtual reality and augmented reality and other fields. [0003] Eye tracking technology is divided into two parts: extraction of eye feature parameters and establishment of gaze estimation model. Among them, the extraction of eye feature parameters is a necessary process and premise of eye tracking, and the quality of feature parameter extraction is directly related to the accuracy of gaze estimation. The extraction of eye fe...

AI Technical Summary

Problems solved by technology

[0005] The bracket of the eye movement data collector is mechanically fixed. In order to ensure that the subject’s eyes are within the image range of the eye movement camera, the height and elevation angle of the bracket need to be manually adjusted each time according to the subject’s height and body posture. Inconvenient to use, poor adaptability to different subjects, and in the adjustment process, good cooperation between the debugger and the testee is required to ensure the final detection accuracy, otherwise it will have a great impact on the test results. If it is not timely, it needs to be adjusted again, resulting in extremely low efficiency, poor precision, and poor adaptability

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