Pupil center-corneal reflection (PCCR) based sight line evaluation method in sight line tracking system

Abstract

The invention provides a pupil center-corneal reflection (PCCR) based sight line evaluation method in a sight line tracking system, belonging to the field of man-machine interaction. With specific to the main problems on user head motion limits and individual calibration in the traditional PCCR, the invention provides a method for compensating head positions under the conditions of a single camera and a single light source, which realizes the analysis compensation for influences of head positions variation to a pupil center-corneal vector, establishes an individual difference conversion model and further simplifies a calibration process to be a single-point process. Accordingly, a novel sight line evaluation method is developed; and in the method, the requirements of precise sight line evaluation on minimum hardware are decreased to be the single camera (uncalibrated) and the single light source, complex system calibration is unnecessary, natural head-motion sight line evaluation is realized, and user calibration is simplified to be single-point calibration. All links in the method meet the instantaneity requirements, and an effective solution to the sight line tracking system oriented to man-machine interaction is provided.

Description

technical field [0001] The invention relates to a line-of-sight estimation method based on pupil-corneal reflection (PCCR) in a line-of-sight tracking system, which belongs to the field of human-computer interaction. Background technique [0002] Gaze tracking technology is a technology that uses mechanical, electronic, optical and other detection methods to obtain the current "gaze direction" of the subject. According to the system composition and detection methods used, it can be roughly divided into two types: invasive and non-invasive. It has a wide range of applications in the fields of human-computer interaction and disease diagnosis, such as disability assistance, virtual reality, cognitive impairment diagnosis, vehicle assisted driving, human factor analysis, etc. Gaze-tracking systems for diagnostics can be invasive for greater precision. In addition to the accuracy, robustness, and real-time requirements of the eye-tracking system for interaction, it is necessary ...

AI Technical Summary

Problems solved by technology

In addition, no practical systems have been built using this technology

[0010] The 3D gaze estimation method has the following disadvantages: (a) In the existing 3D gaze estimation methods, either independent information about the user's eye parameters is required, or a complex hardware configuration with at least two cameras and two light sources is required

But if the head moves away from the user's calibrated position, the accuracy of the gaze tracking system will drop significantly

[0013] The two-dimensional line of sight estimation method has the following disadvantages: (a) The two-dimensional line of sight estimation depends on the calibration position, and the accuracy of the line of sight estimation decreases rapidly as the user's head moves away from the calibration position, so the user needs to keep the head still

However, none of the existing line-of-sight estimation methods can fully meet the above requirements.

There are two common shortcomings in the direct 3D line-of-sight estimation methods: first, a complex hardware configuration of at least two cameras (calibrated) and two light sources is required; second, the complicated system calibration process

The existing estimation methods based on two-dimensional mapping models all have two common shortcomings: first, the user needs to perform multi-point individual calibration before use; second, the user needs to keep the head still

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