Eye-movement tracking method and system based on recalling and annotation

Abstract

The invention provides an eye-movement tracking method based on recalling and annotation. The eye-movement tracking method comprises the following steps: (1) defining a recalling and annotation manner of a user and setting a corresponding task; (2) representing a task instruction on a display screen and publishing the task to the user; (3) presenting an image stimulating source on the display screen; (4) allowing the user to observe the image stimulating source on the display screen according to task requirements; (5) allowing the user to recall fixation points generated in a task executing process according to the task requirements and annotate coordinate positions and a sequence of the fixation points on the display screen; if entering a training mode, skipping to step (6); if entering a normal mode, skipping to step (8); (6) not representing the image stimulating source, which is represented to the user by the training mode, to the user in the normal mode; (7) evaluating training performances of the user; and (8) when the user enters the normal testing mode, recording andstoring fixation point positions annotated by the user and sequence data thereof. The invention further provides a system utilizing the method.

Description

technical field [0001] The present invention relates to the fields of human-computer interaction, visual cognition, social computing, etc., and in particular to an eye tracking method and system based on memory and annotation. Background technique [0002] At present, in many scientific researches and commercial applications, such as psychology, advertising design, ergonomics, etc., people need to study the user's eye movement behavior when observing things, such as the position of the fixation point and the trajectory of the movement, for further analysis of visual attention space-time distribution. [0003] Existing methods mainly use optical eye movement tracking methods to obtain eye movement data such as gaze points. The main process is to use a camera device to capture human eye images, use image processing methods to extract eye image related features, and then establish eye image features. The mapping relationship with the eye movement behavior is finally calculated...

AI Technical Summary

Problems solved by technology

[0004] However, this type of method mainly has the following defects: First, the eye-tracking system has a complex structure, high hardware and software costs, and is difficult to popularize.

Second, the use process of the eye tracking system is complicated, and the user must perform it under the guidance of professional technicians, and before collecting data, the user needs to perform the data calibration process, and during the data collection process, the user also needs to minimize head movement

Third, the data collection efficiency of the eye-tracking system is low. An eye-tracking system can only collect eye-movement data of one user at a time. In addition, the use process is complicated, and it is impossible to collect a large number of effective data in a short period of time. eye movement data

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