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研究生: 洪銘陽
Hung, Ming-Yang
論文名稱: 具頭動補償之可見光雙眼眼動儀系統
Visible Light Binocular Gaze Tracker with Head Movement Compensation
指導教授: 高文忠
Kao, Wen-Chung
學位類別: 碩士
Master
系所名稱: 電機工程學系
Department of Electrical Engineering
論文出版年: 2018
畢業學年度: 106
語文別: 中文
論文頁數: 74
中文關鍵詞: 可見光眼動儀雙眼追蹤眼角追蹤頭動補償
英文關鍵詞: visible light gaze tracker, binocular tracking, canthus tracking, head movement compensation
DOI URL: http://doi.org/10.6345/THE.NTNU.DEE.001.2018.E08
論文種類: 學術論文
相關次數: 點閱:165下載:0
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  • 眼動儀是未來智慧型電子產品的重要人機互動介面,可以用於分析使用者的關注點以及意圖。自然光源眼動儀於眼睛定位與虹膜中心位置的計算均較紅外光眼動儀困難。但因為紅外線光源近距離照射觀看者的眼睛,長時間使用將導致眼睛疲勞,且無法在戶外太陽光下使用。反之,可見光眼動儀無須外加光源,未來有機會成為消費性電子產品的基本輸入配備。然而,因為可見光源的變化相當大,導致眼睛影像的特徵有相當的差異,使得偵測瞳孔困難,遂改以虹膜異色邊緣取代之,再計算最適合的橢圓方程式,推算眼球中心的座標,加入頭動補償資訊,修正偏移的眼球中心,最後映射到螢幕上,得知使用者的目光凝視焦點。

    The gaze tracking system is designed to analyze the intentions and interests of the user. There are problems of a gaze tracking system with visible light, such as detecting the region of the pupil and accurately identifying the center of iris region, which appear to be more difficult than gaze tracking system with IR light. However, the illumination from IR light sources not only makes the user feel uncomfortable with their eyes, but fails in an outdoor environment. In contrast, the visible light gaze tracker could be operated smoothly without an extra IR light sources. It is expected the visible light gaze tracker will become a general input device integrated with the smart consumer electronics or other specific devices. However, the main challenge of visible gaze tracker is the difficulty in detecting the pupil location caused by the variations of the illumination. Instead, the system can only detect the limbus circle and estimate the center of the eyeball by fitting the model with the shape of the detected limbus circle. This study aims to compensate the error according to the information of head movement, and then calculate where the user is reading.

    摘要 i ABSTRACT ii 誌謝 iii 目錄 iv 圖目錄 vii 表目錄 xi 第一章 緒論 1 1.1 研究背景 1 1.2 眼動儀於市場的應用 2 1.3 研究問題 3 1.4 論文架構 4 第二章 文獻探討 5 2.1 虹膜辨識與追蹤方法 5 2.1.1 以特徵為基礎的演算法 5 2.1.2 以模型為基礎的演算法 7 2.2 頭動校正 10 2.3 眼角搜尋 12 2.4 物件追蹤 14 2.5 本論文選擇的方法 16 第三章 提出系統架構 17 3.1 系統訊號流程 19 3.2 眼球模型參數初始化 20 3.2.1 虹膜圓位置初始化 21 3.2.2 虹膜圓位置最佳化 27 3.2.3 眼角位置初始化 30 3.3 凝視點校正 35 3.3.1 眼角追蹤 36 3.3.2 五階段虹膜圓追蹤 39 3.3.3 建立映射方程式 43 3.3.4 建立視角補償方程式 44 3.4 凝視點驗證 47 3.4.1 視角補償 48 3.4.2 映射 48 第四章 實驗設計與結果 49 4.1 實驗設備、實驗環境設置與實驗流程設計 49 4.1.1 實驗設備 49 4.1.2 實驗環境設置 51 4.1.3 實驗操作流程設計 51 4.1.4 系統限制 52 4.2 眼動儀系統性能評估方式 52 4.2.1 系統精準度 53 4.2.2 系統穩定度 53 4.3 虹膜圓位置最佳化之必要性與成果 54 4.4 頭動補償成果 56 4.4.1 本論文所提出方法進行眼睛定位 56 4.4.2 利用壓縮追蹤進行眼睛定位 60 4.5 視角補償成果 63 4.6 整體系統精準度比較 67 第五章 結論與未來展望 69 5.1 結論 69 5.2 未來展望 69 參考文獻 71 自傳 73 學術成就 74

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