Analysis And Design Of Virtual Video Eye Movement

Eye tracking technology has a broad application prospect in the field of human-computer interactive interface,the disabled,fatigue test,aviation medical research etc..Head movement is an important accompanying behavior in the process of gaze fixation,which is of great significance to human visual attention.In this paper,the study of eye movement analysis technology,based on facial recognition and feature analysis,we improve the eye tracking method and head motion tracking method for eye tracking,this paper uses the non wearable wide field infrared camera to obtain images of human face,realize the face recognition using Adaboost algorithm,and then use the ASM algorithm for real-time tracking of facial features and image acquisition.The interception of eye region image,and then through the Hof transform algorithm and image threshold processing to acquire and track the Purkinje image and pupil eye area in the image,the four light source is improved through visual method,the establishment of four light Purkinje image and pupil relationship model,through the polynomial to obtain estimates of eye gaze point.For head motion tracking,the tracking of head motion based on inertial sensor and POSIT camera is adopted in this paper.First,the four order Runge Kutta method,Picard approximation and interpolation integral acceleration,realize the attitude motion of inertial sensor tracking.Then the POSIT iterative algorithm is used to solve the problem.Finally,according to the characteristics of the two methods,learn from each other through data fusion,and effectively improve the efficiency of measuring head motion tracking.Finally,this paper combines the software architecture to achieve a non wearable head movement and gaze tracking data fusion measurement system.The system is composed of a plurality of software components,the input data is sent to the component through the connector,and the required data is output.Finally constitute a complete set of functions of the software.