Research On Device Design And Pupil Tracking Algorithm Of Wireless Video Eye Tracker

The eye has always been regarded as a bridge between the human body and the outside world.It can not only obtain various information of the outside world,but also reflect some physiological and psychological states in the human body.Therefore,since ancient times,the research and attention of the eyeball has never been stopped,and eye tracker is an auxiliary tool for the study of the eyes.As a device that can detect and record the relative state of the human eye,eye tracker is widely studied and used in many fields such as Psychology,Medicine and Human-computer interaction.However,at present,eye tracker is mainly imported from abroad,and the price is expensive,which is not conducive to popularization and promotion.On this background,this paper developed a complete set of eye tracker devices and background software analysis system by combining hardware and software technology,3D printing technology,image processing algorithm,etc.And then,the feasibility of the device and related processing algorithm is verified by collecting and analyzing eye movement images using our eye tracker.The main work of this paper is as follows.(1)Based on the research and analysis of wireless technology,the hardware circuit of wireless video eye tracker is completed by using the existing efficient routing module and designed peripheral circuit.And then,the improvement is made by combining the using effect to meet the use requirement.Because the production made by 3D printing technology have high precision and simple production process,stereo lithography apparatus(SLA)is used to make the eye tracker based on the size of each module of the hardware circuit.Then,according to the feedback in the process of wearing,the device is improved.The final eye tracker can basically meet the requirements of different people,and the appearance is beautiful and easy to carry.(2)The data collected by eye tracker is inevitable to be accompanied with some noise in some acquisition situations.Therefore,image denoising is needed to further pupil location and tracking.Denoising has always been a hotspot in image processing research.And based on the research of the nonlocal algorithm,an improved NLM method is proposed in this paper.Firstly,the wavelet threshold denoising theory is used to pre-filter out some noise without destroying the image quality.Then,an adaptive weight function is used in NLM filter to better save image edges and improve the denoising effect.After image denoising finished,in order to accurately extract the pupil area,some researches about segmentation methods including Otsu method,bottom minimum method,the minimum threshold method based on the bottom of gray scale have been done to find out adaptive binary image segmentation algorithm which can be applied to the infrared eye movement image.After image's binarization,the median filter algorithm and four step morphological processing was used to complete the pretreatment of infrared eye image.Through the above treatments,the image noise,some lights,eyebrows,eyelids and other distractions can be removed.(3)After image's pretreatment,a fast connected domain detection method is developed in this paper.The method makes full use of the connectivity features of the four pixels in the left and top of each pixel,which can complete the detection and marking of all connected regions with only once scanning.Then,according to the shape and size of the pupil,the pupil area can be found in the connected regions.The external rectangular heart of the connected pupil area is identified as the center of the pupil.This method is fast and accurate,and can be used in continuous positioning tracking of multi-frame video.(4)In the software environment of vc6.0,the software development kit(SDK)of hardware circuit and the verified feasibility eye tracking algorithm in matlab is used to complete the Windows platform analysis system of the eye tracker device.The software system can realize the communication with eye tracker device and infrared eye movement images can be collected with fixed resolution through WiFi,and it can accurately locate and track the pupil movement.