本文選題：視線追蹤　切入點(diǎn)：頭部運(yùn)動(dòng)　出處：《西安工業(yè)大學(xué)》2017年碩士論文　論文類型：學(xué)位論文

【摘要】：視線追蹤技術(shù)在人機(jī)界面交互、助殘、疲勞駕駛檢驗(yàn)、航空醫(yī)學(xué)研究等領(lǐng)域有廣泛的應(yīng)用前景。頭部運(yùn)動(dòng)是人視線注視過程中的重要的伴隨行為,對(duì)于人類視覺注意有著重要的意義。通過數(shù)據(jù)融合技術(shù)將頭部運(yùn)動(dòng)和視線跟蹤放在一起研究,開拓了視線追蹤系統(tǒng)高效性、可靠性、可使用性和功能性提高的新思路。本文針對(duì)頭部運(yùn)動(dòng)與視線追蹤數(shù)據(jù)融合技術(shù)的研究,首先改進(jìn)視線追蹤方法和頭部運(yùn)動(dòng)跟蹤法:對(duì)于視線跟蹤,本文采用非穿戴式寬視野紅外相機(jī)獲取人面部圖像,通過Adaboost算法實(shí)現(xiàn)面部識(shí)別,然后采用ASM算法對(duì)獲取的面部圖像進(jìn)行實(shí)時(shí)特征跟蹤,并截取眼球區(qū)域圖像,然后通過霍夫變換算法和圖像閾值處理獲取并跟蹤眼球區(qū)域圖像中普爾欽斑和瞳孔中心,最后采用改進(jìn)的四光源透視法,建立四光源普爾欽斑與瞳孔關(guān)系模型,通過多項(xiàng)式估計(jì)獲得視線注視點(diǎn)。對(duì)于頭部運(yùn)動(dòng)跟蹤,本文同時(shí)采用基于慣性傳感器和基于POSIT攝像機(jī)觀測(cè)法的頭部姿態(tài)空間運(yùn)動(dòng)的跟蹤。首先本文通過四階龍格庫塔法、畢卡逼近和加速度插值積分,實(shí)現(xiàn)慣性傳感器的姿態(tài)運(yùn)動(dòng)跟蹤。然后通過POSIT迭代算法對(duì)圖像進(jìn)行解算獲得頭部運(yùn)動(dòng)信息。最后結(jié)合兩種方法的特點(diǎn),通過數(shù)據(jù)融合,取長(zhǎng)補(bǔ)短,有效提高頭部運(yùn)動(dòng)跟蹤測(cè)量效率。本文對(duì)數(shù)據(jù)融合技術(shù)進(jìn)行理論研究,提出了數(shù)據(jù)融合機(jī)的概念,以及結(jié)合神經(jīng)網(wǎng)絡(luò)算法等智能方法實(shí)現(xiàn)數(shù)據(jù)融合系統(tǒng)的構(gòu)建。基于理論研究,將獲取的眼動(dòng)數(shù)據(jù)和頭部運(yùn)動(dòng)數(shù)據(jù)進(jìn)行融合處理,從而獲得視線跟蹤系統(tǒng)的頭部補(bǔ)償與視線空間方向數(shù)據(jù),為頭眼協(xié)調(diào)等應(yīng)用提供測(cè)量工具。最后,本文結(jié)合軟件體系結(jié)構(gòu),實(shí)現(xiàn)了非穿戴式的頭部運(yùn)動(dòng)與視線追蹤數(shù)據(jù)融合測(cè)量系統(tǒng)。系統(tǒng)由多個(gè)軟件構(gòu)件構(gòu)成,輸入數(shù)據(jù)通過連接件傳入構(gòu)件,輸出所需要的數(shù)據(jù),構(gòu)成一套具備完整功能的軟件。
[Abstract]:Eye tracking technology has a wide application prospect in the fields of man-machine interface interaction, disability, fatigue driving test, aeronautical medical research, etc. Head movement is an important accompanying behavior in the process of human visual gaze. It is of great significance to human visual attention. Through data fusion technology, the head motion and line of sight tracking are studied together to develop the high efficiency and reliability of the line of sight tracking system. This paper aims at the research of head motion and line of sight tracking data fusion technology, first improve the line of sight tracking method and head motion tracking method: for line of sight tracking, In this paper, a non-wearable wide-field infrared camera is used to obtain human facial image, and Adaboost algorithm is used to realize facial recognition. Then, ASM algorithm is used to track the real-time features of the acquired facial image and to capture the eyeball region image. Then, by means of Hough transform algorithm and image threshold processing, Pulchin spot and pupil center in the eye region image are obtained and tracked. Finally, an improved four-light source perspective method is used to establish the model of the relationship between the four light source Purchin spot and the pupil. For head motion tracking, both inertial sensor and POSIT camera observation method are used to track the head attitude spatial motion. Firstly, the fourth order Runge-Kutta method is used in this paper. The attitude tracking of inertial sensor is realized by using Bika approximation and acceleration interpolation integral. Then the head motion information is obtained by POSIT iterative algorithm. Finally, combining the characteristics of the two methods, we learn from each other by data fusion. In this paper, the data fusion technology is studied theoretically, the concept of data fusion machine is put forward, and the intelligent method such as neural network algorithm is used to realize the construction of data fusion system. The obtained eye movement data and head motion data are fused to obtain the head compensation and line of sight spatial direction data of the line of sight tracking system, which provides a measurement tool for head-eye coordination and other applications. Finally, this paper combines the software architecture, A non-wearable head motion and line of sight tracking data fusion measurement system is implemented. The system is composed of several software components. The input data is transmitted to the components through the connectors and the required data is outputted to form a set of software with complete functions.
【學(xué)位授予單位】：西安工業(yè)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TP391.41

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