Eye movement track recognition method and device apparatus based on textural features

Abstract

The invention provides an eye movement track recognition method and apparatus based on textural features. By acquiring an original eye movement track diagram recorded by an eye tracker and extracting features of the original eye movement track diagram, the extracted features are input into a classifier; a recognition result is acquired; and by carrying out recognition on the original eye movement track diagram, texture details of an eye movement track are more abundant, so that the recognition accuracy rate is improved.

Description

Technical field [0001] The present invention relates to image processing technology, in particular to a method and device for recognizing eye movement tracks based on texture features. Background technique [0002] Biometric identification refers to the technology that uses the inherent characteristics of the human body to perform identity identification through a computer. Eye tracking recognition technology is widely used in the unique psychological mechanism of identity authentication and personal visual information processing. [0003] In the prior art, the eye movement trajectory recognition method is based on the characteristics of fixation point and saccade, namely "complex eye movement pattern biometrics", "complex eye movement pattern biometrics" is based on fixation point and saccade trajectory The gaze point and saccade trajectory map is based on the gaze point and saccade data, so the obtained gaze point and saccade trajectory are very sparse. Among them, the eye track...

AI Technical Summary

Problems solved by technology

[0003] In the prior art, the eye movement trajectory recognition method is based on the characteristics of fixation points and saccades, that is, "complex eye movement pattern biometrics", and "complex eye movement pattern biometrics" is based on fixation points and saccade trajectories The feature extracted from the graph, while the fixation point and saccade trajectory graph is based on the gaze point and saccade data, so the obtained fixation point and saccade trajectory are very sparse. Among them, the eye tracker obtains the original data of the eye movement trajectory graph, Assuming that the sampling rate of the eye tracker is 300HZ, the fixation point refers to the point where the interval between the current sampling point and the next adopting point is greater than or equal to a preset threshold, which is usually 200ms, and the saccade refers to the point between two fixation points. The fast-moving points in between, because the fixation point and eye saccade are artificially divided based on the original eye movement data, and the obtained fixation point and eye saccade trajectory is very sparse, so the recognition accuracy is low

Images