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人機介面 視線軌跡追蹤 : 原理與應用

人機介面 視線軌跡追蹤 : 原理與應用. 授課教師 開課單位. Outline. 眼動儀類型 應用領域與最新技術 Application areas State-of-the-art technology Eye tracker @NCCUCS 1.0 (wearable) Eye tracker @NCCUCS 2.0 (remote) Gaze-based HCI Demo ( 展示 ) Conclusions. 眼動儀類型. 侵入式 搜尋線圈法（ Search Coil ） 眼電圖法（ Electro- Oculography ） 非侵入式

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人機介面 視線軌跡追蹤 : 原理與應用

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  1. 人機介面視線軌跡追蹤: 原理與應用 授課教師 開課單位

  2. Outline • 眼動儀類型 • 應用領域與最新技術 • Application areas • State-of-the-art technology • Eye tracker @NCCUCS 1.0 (wearable) • Eye tracker @NCCUCS 2.0 (remote) • Gaze-based HCI Demo(展示) • Conclusions

  3. 眼動儀類型 • 侵入式 • 搜尋線圈法（Search Coil ） • 眼電圖法（Electro-Oculography） • 非侵入式 • 紅外線視訊（Infra-red Video System） • 光學式瞳位追蹤(Optical-type Eye Tracking Device) • 紅外線眼動圖法（Infra-red Oculography） • Purkinje 影像追蹤法（Dual-Purkinje-image）

  4. 搜尋線圈法 • 利用電磁感應的原理來測量眼球的移動 優點： • 有很好的空間和時間解析度 缺點： • 需戴上侵入式鏡片 • 受到眼球分泌物的影響 • 固定磁場 搜尋線圈法四週固定磁場示意圖

  5. 眼電圖法 • 利用電極的原理來測量眼球的移動 優點： • 價格便宜 缺點： • 必須貼電極貼在皮膚上 • 皮膚角質分泌影響皮膚電阻

  6. 紅外線視訊系統 優點： • 可計算瞳孔移動位置和大小 缺點： • 價格昂貴 • 空間位置校正 影像追蹤的方法記錄眼球的移動

  7. 光學式瞳位追蹤系統 優點： • 使用者頭部與攝影機之間的相對位置不會改變 缺點： • 頭盔因本身重量往下滑 • 光源讓人不舒服 • 配戴眼鏡無法使用 第四代追瞳器裝置 由攝影機所獲得的瞳孔影像，利用影像處理的方式，分析眼球的移動軌跡

  8. 紅外線眼動圖法 優點： • 測量範圍廣 缺點： • 紅外線光對眼睛可能會造成傷害 利用紅外線光源在眼角膜邊緣的反射差異，來檢測眼球運動狀況

  9. Purkinje 影像追蹤法 優點： • 不易受眼瞼遮蔽準確度高 缺點： • 不能和眼球同步 • 價格極為昂貴 光源經過眼球組織不同的折射率，來計算眼球運動

  10. 應用領域 • 醫療: 漸凍人等身體障礙者輸入介面 • EyeMusic - 創作音樂 • EyeDraw - 繪畫 • Usability: 網頁和廣告的使用性和實用性 • 電腦 - 替代滑鼠，文字輸入 • 遊戲 - eye tracking game • 心理學 - 眼球測謊儀 • 閱讀 - text 2.0 • 遠端遙控 - 遠端電視操控，EyeTech

  11. 基於影像之眼動追蹤 • An eye tracker is a device for measuring eye positions and eye movements. • The most popular variant uses video images from which the eye position is extracted. • Input source: visible spectrum vs. infrared

  12. 眼動 Eye Movements • Eye movements are typically divided into fixations(凝視when the eye gaze pauses in a certain position) and saccades (掃視 when it moves to another position). • The resulting series of fixations and saccades is called a scanpath. (掃描路徑)

  13. 掃描路徑實例

  14. 阿春眼動看護

  15. EyeWriter Project

  16. Web Design (U. of Manchester) Heat map Gaze plot

  17. Usability Study:Google Search Evaluation

  18. Gaming

  19. Driving Behavior [Andrew T. Duchowski]

  20. Character Input EyeWrite [Andrew T. Duchowski]

  21. Media Research • The Poynter Institute : http://www.poynter.org • Published first eye track study in 1991. • More results published in 2000, 2004 and 2007. • Eyetrack ’07:http://www.poynter.org/content/content_view.asp?id=105035

  22. Text 2.0

  23. Research Communities • ACM SIG/CHI • Eye Tracking Research and Applications (ETRA) Symposium: http://www.e-t-r-a.org/ • COGAIN: Communication by Gaze Interaction http://www.cogain.org • References: http://www.cogain.org/downloads/

  24. State-of-the-art Eye tracking Technology • Hi-Speed (SMI iView X™ Hi-Speed) • Head-Mounted System • Remote tracking • Integrated with LCD monitor • Wearable glasses

  25. Mobile Eye Tracker 1.0 @ NCCUCS scene camera eye camera

  26. Key Objectives • Low-cost (NTD 10,000 vs. 1,000,000) • Mobility • Easily customized for specific applications • On-line processing • Sampling rate? • Accuracy?

  27. System Architecture Eye image Calibration process Preprocessing 9 pairs of points Pupil detection Calibration Gaze point projection Scene image

  28. Pupil Detection (I):extracting feature points

  29. Pupil Detection (II): Ellipse fitting using RANSAC

  30. Pupil Detection (III):checking fitness measure • Ellipse model: Number of bright vs. dark points inside and out the perimeter

  31. Results

  32. HCI Application: Eye Scrolling

  33. HCI Application: Eye Gaming

  34. HCI Application: Eye Typing

  35. Mobile Eye Tracker 2.0 @ NCCUCS • Improve the pupil detection algorithm to alleviate corneal reflection problem. • Enhance the accuracy by compensating for head movement. • Construct and test a remote eye tracker. • More HCI applications using the remote eye tracker. • Use the eye tracking device to assist mobile user interface design.

  36. Improved Pupil Detection

  37. Allowing Head Movement

  38. Remote Eye Tracker

  39. Experimental Results (Wearable) 1 cm = 38 Pixels

  40. Accuracy (Wearable)

  41. Experimental Results (Remote)

  42. Accuracy (Remote Eye Tracker)

  43. Demo: Web Browsing

  44. Demo: Photo Viewing

  45. Demo: Interactive Story Telling

  46. Demo: Tic-Tac-Toe

  47. Gaze Path Analysis • Recursive intersection • Find the similarity between two scan paths • Order of scanning is irrelevant • Suitable for processing fixation data • Modified dynamic time warping • Order of scanning is taken into account • Can handle both fixation and saccade data

  48. Path 1 Path 2 Recursive Intersection

  49. Recursive Intersection: Example

  50. Dynamic Time Warping (DTW)

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