本文選題：角膜曲率中心 + 瞳孔中心��； 參考：《西安電子科技大學(xué)》2015年碩士論文

【摘要】：視線跟蹤技術(shù)是通過(guò)采集實(shí)時(shí)眼動(dòng)信息來(lái)實(shí)現(xiàn)對(duì)用戶眼睛注視方向的估計(jì),進(jìn)而得到其視線落點(diǎn)的一種方法。隨著科學(xué)技術(shù)的不斷發(fā)展,視線跟蹤系統(tǒng)作為一種新型的人機(jī)交互設(shè)備,廣泛應(yīng)用于生物工程、道路交通、廣告設(shè)計(jì)、心理分析等領(lǐng)域。目前,3D桌面式視線跟蹤系統(tǒng)具有不需要用戶佩戴任何設(shè)備且允許用戶有較大的頭動(dòng)范圍等優(yōu)點(diǎn)而受到廣泛關(guān)注,成為視線跟蹤技術(shù)中的一個(gè)主要研究方向。3D視線跟蹤技術(shù)雖然發(fā)展迅速,但還有許多尚未解決的問(wèn)題,本文主要對(duì)3D視線跟蹤系統(tǒng)中的數(shù)學(xué)模型與算法進(jìn)行了研究,具體工作如下:1.求解角膜曲率中心的混合智能算法。本文首先將角膜曲率中心的非線性方程組模型轉(zhuǎn)化為無(wú)約束優(yōu)化模型(CCCUO)及改進(jìn)的優(yōu)化模型(MCCCUO),然后結(jié)合遺傳算法和LM算法,提出了一種混合智能算法(GALM算法),即先用遺傳算法進(jìn)行全局搜索求出一個(gè)近似解,再將此解作為初始值,用LM算法進(jìn)一步求得更高精度的解。運(yùn)用GALM算法分別求解兩種優(yōu)化模型,并與遺傳算法進(jìn)行了比較。實(shí)驗(yàn)結(jié)果表明了GALM算法優(yōu)于遺傳算法,提高了解的精度,減少了計(jì)算時(shí)間。2.瞳孔中心非線性方程組模型的求解。首先求出角膜表面折射點(diǎn)的坐標(biāo),然后針對(duì)瞳孔中心的非線性方程組模型對(duì)解的約束不強(qiáng)導(dǎo)致存在4個(gè)解的缺陷問(wèn)題,對(duì)模型進(jìn)行了改進(jìn),增加了兩個(gè)不等式約束條件,最后根據(jù)瞳孔中心和角膜曲率中心的位置關(guān)系設(shè)置初始值,運(yùn)用LM算法求出瞳孔中心的準(zhǔn)確位置。3.角膜曲率中心模型的魯棒性分析。首先將其非線性方程組線性化,通過(guò)近似線性方程組的條件數(shù)來(lái)衡量病態(tài)性,結(jié)果表明非線性方程組模型對(duì)參數(shù)變化非常敏感。然后對(duì)角膜曲率中心模型的兩種優(yōu)化模型采用相同的參數(shù)擾動(dòng)進(jìn)行測(cè)試。數(shù)值實(shí)驗(yàn)表明無(wú)約束優(yōu)化模型(CCCUO)魯棒性差,而改進(jìn)的優(yōu)化模型(MCCCUO)受參數(shù)擾動(dòng)的影響較小,魯棒性較好。
[Abstract]:Line of sight tracking technology is a method to estimate the gaze direction of the user by collecting real-time eye movement information, and then to get the location of the eye sight.With the development of science and technology, line of sight tracking system, as a new type of human-computer interactive equipment, is widely used in bioengineering, road traffic, advertising design, psychological analysis and other fields.At present, 3D desktop line of sight tracking system has the advantages of not requiring the user to wear any device and allowing the user to have a large head-moving range and so on.Although it has developed rapidly, there are still many unsolved problems. In this paper, the mathematical model and algorithm of 3D line of sight tracking system are studied.The work is as follows: 1.A hybrid intelligent algorithm for solving corneal curvature centers.In this paper, the nonlinear equations model of corneal curvature center is first transformed into an unconstrained optimization model (CCCUO) and an improved optimization model (MCCCUOO), which is then combined with genetic algorithm and LM algorithm.In this paper, a hybrid intelligent algorithm (GALM) is proposed, in which an approximate solution is obtained by global search with genetic algorithm, then the solution is taken as the initial value, and a higher precision solution is obtained by using LM algorithm.Two optimization models are solved by GALM algorithm and compared with genetic algorithm.The experimental results show that the GALM algorithm is superior to the genetic algorithm, improves the accuracy of the solution, and reduces the computing time. 2.The solution of the nonlinear equations of pupil center.The coordinate of refraction point on corneal surface is obtained first, and then two inequality constraints are added to improve the model for the defect of four solutions caused by the constraint of the nonlinear equations model in the center of pupil.Finally, according to the relationship between the center of pupil and the center of corneal curvature, the initial value is set, and the exact position of pupil center is calculated by LM algorithm.Robustness analysis of corneal curvature center model.Firstly, the nonlinear equations are linearized, and the ill-condition is measured by approximating the condition number of linear equations. The results show that the nonlinear equations model is very sensitive to the change of parameters.Then the two optimization models of corneal curvature center model were tested with the same parameter disturbance.Numerical experiments show that the unconstrained optimization model (CCCUO) has poor robustness, while the improved optimization model (MCCCUO) is less affected by parameter disturbances and has better robustness.
【學(xué)位授予單位】：西安電子科技大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2015
【分類號(hào)】：TP391.41;O241.7;TP18

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 陳世明;龐少鵬;鄒小群;方華京;陳曜;;面向級(jí)聯(lián)失效的加權(quán)網(wǎng)絡(luò)負(fù)載容量非線性模型魯棒性優(yōu)化[J];控制與決策;2013年07期

2 溫晴川;達(dá)飛鵬;方旭;;基于雙目立體視覺的視線跟蹤系統(tǒng)標(biāo)定[J];光學(xué)學(xué)報(bào);2012年10期

3 李海瓊;秦雅琴;;眼動(dòng)儀在道路交通領(lǐng)域中的應(yīng)用[J];人類工效學(xué);2012年02期

4 李斐;郝衛(wèi)峰;王文睿;張杰;;非線性病態(tài)問(wèn)題解算的擾動(dòng)分析[J];測(cè)繪學(xué)報(bào);2011年01期

5 趙新燦;盧朝陽(yáng);;頭部自由運(yùn)動(dòng)的視線跟蹤方法[J];南京航空航天大學(xué)學(xué)報(bào);2010年04期

6 陽(yáng)萬(wàn)安;曾安平;;求解復(fù)雜非線性方程組的新方法[J];計(jì)算機(jī)工程與應(yīng)用;2009年28期

7 付振岳;王順?lè)?;改進(jìn)的遺傳退火算法在針對(duì)含有超越函數(shù)的非線性方程組中求解的應(yīng)用[J];云南大學(xué)學(xué)報(bào)(自然科學(xué)版);2009年S1期

8 彭靈翔;李于鋒;;用實(shí)數(shù)編碼遺傳算法解非線性方程組[J];延安大學(xué)學(xué)報(bào)(自然科學(xué)版);2007年02期

9 王冬冬;周永權(quán);;人工魚群算法在求解非線性方程組中的應(yīng)用[J];計(jì)算機(jī)應(yīng)用研究;2007年06期

10 楊平;鄭金華;;遺傳選擇算子的比較與研究[J];計(jì)算機(jī)工程與應(yīng)用;2007年15期

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