Particle filtering-based pupil tracking method in sight tracking system

Abstract

The invention discloses a particle filtering-based pupil tracking method in a sight tracking system and belongs to the field of human-computer interaction. Aiming at a problem that the pupil tracking efficiency in the conventional infrared image is poor, the method creates a concept of a tri-channel pseudo color image (TCPCM) which fully uses information of each channel, enables the characteristics of a pupil to be obvious, and improves the stability and the accuracy of tracking. Aiming at a problem that a background interferes in a pupil tracking process, the method creates a pupil object model which accords with the morphological characteristics and change rules of the pupil to fully differentiate the front background from the back background so as to decrease the interference of the background to the object model. Aiming at a problem that the prediction effect of the position and the form of the pupil is poor, the method creates a state transition equation embodying the motion rules of the pupil, fully considers various conditions of the state change of the pupil and can effectively predict the position and shape of the pupil. Through high-quality characteristic detection and tracking, the method enables the precision of a developed sight tracking system to reach a level of real-time human-computer interaction.

Description

technical field [0001] A pupil tracking method based on a particle filter in a gaze tracking system belongs to the field of human-computer interaction, and in particular relates to a face feature detection and tracking method in a human-computer interaction system. 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-...

AI Technical Summary

Problems solved by technology

But doing so has the following two problems: (a) each time the pupil is searched in the entire image, the efficiency is low, the time is long, and the real-time performance of the system is affected

[0008] The Kalman filter method approximates the nonlinear motion of the target by means of parameterization. The main disadvantage is that the requirements for the filtering error and measurement error of the system are relatively strict. If these requirements cannot be met, the tracking may fail. stable or even complete failure

Images