博碩士論文 90532004 詳細資訊




以作者查詢圖書館館藏 以作者查詢臺灣博碩士 以作者查詢全國書目 勘誤回報 、線上人數:36 、訪客IP:3.139.82.23
姓名 王國強(Guo-chiang Wang)  查詢紙本館藏   畢業系所 資訊工程學系在職專班
論文名稱 人眼追蹤系統及其於人機介面之應用
(An Eye-Tracking System and Its Application in Human Computer Interfaces)
相關論文
★ 以Q-學習法為基礎之群體智慧演算法及其應用★ 發展遲緩兒童之復健系統研製
★ 從認知風格角度比較教師評量與同儕互評之差異:從英語寫作到遊戲製作★ 基於檢驗數值的糖尿病腎病變預測模型
★ 模糊類神經網路為架構之遙測影像分類器設計★ 複合式群聚演算法
★ 身心障礙者輔具之研製★ 指紋分類器之研究
★ 背光影像補償及色彩減量之研究★ 類神經網路於營利事業所得稅選案之應用
★ 一個新的線上學習系統及其於稅務選案上之應用★ 結合群體智慧與自我組織映射圖的資料視覺化研究
★ 追瞳系統之研發於身障者之人機介面應用★ 以類免疫系統為基礎之線上學習類神經模糊系統及其應用
★ 基因演算法於語音聲紋解攪拌之應用★ 虹膜辨識系統之研究與實作
檔案 [Endnote RIS 格式]    [Bibtex 格式]    [相關文章]   [文章引用]   [完整記錄]   [館藏目錄]   [檢視]  [下載]
  1. 本電子論文使用權限為同意立即開放。
  2. 已達開放權限電子全文僅授權使用者為學術研究之目的,進行個人非營利性質之檢索、閱讀、列印。
  3. 請遵守中華民國著作權法之相關規定,切勿任意重製、散佈、改作、轉貼、播送,以免觸法。

摘要(中) 本論文主要目的在介紹如何以低成本方式來實作人眼追蹤系統以及相關的整合技術,運用此套系統可以估算出人眼凝視的方向及位置。而人眼追蹤的應用很廣,其中可應用於幫助殘障者。對於患有肌肉萎縮性脊髓側索硬化症、大腦麻痺、肢體或臉部肌肉無法行動的患者,如果本身的眼睛器官仍然能夠活動自如,患者就可以依賴此追瞳控制系統獲得獨立自主的溝通及控制能力。有幾種人眼追尋的方式是利用光線反射原理、眼動圖資訊(electrooculogram,EOG)或穿戴特殊隱形眼鏡等,其缺點可能包含高複雜度運算、高成本或者具有侵略性質。我們主要目的是為了協助傷殘者更容易操作電腦,並且考慮到價錢以及操作的難易度是兩大阻礙,因此所提出的演算系統不僅操作簡單,而且只需要額外使用一部web camera偵測裝置就能運作。我們提出的人眼偵測演算法概分為五大部份,首先,使用高效率的彩色膚色過濾器,用來分離以及定位使用者的人臉位置,接著運用三個主要求得眼特徵的投影機制將其整合並找出人眼粗略部位,進而使用FCM 演算法定位瞳孔中心點,使用
fuzzy 推論以及九個推論規則計算人眼凝視方向,並將其應用於人機介面的操作。實驗結果證明了此方法不僅快速而且能夠有效率的在複雜背景、移動人臉中執行人眼追尋工作。
摘要(英) The objective of this thesis is to present a set of techniques integrated into a low-cost eye gaze tracking system. An eye gaze tracking
system is a system that estimate the direction of the human’s eye gaze. That is, it finds where a person looks. Although the eye gaze tracking system has many potential applications, one of its main applications is to help the physically and vocally disabled. For some disabled persons, an extreme disability such as severe cerebral palsy or amyotrophic lateral
sclerosis (ALS) deprives them of the use of their limbs and facial muscles.If eye motion is unaffected, the person could rely on an eye gaze tracking system to attain or regain some degrees of independent communication and control. There are several ways of tracking the direction of the
eye-gaze by using reflection of light,electrooculogram (EOG), or contact
lens, etc. Each of them has its own advantages and disadvantages such as high complexity, high cost, and invasive way. Since the main application of the proposed system is to help the disabled to manipulate computers more easily, price and complexity are the two chief considerations. The proposed system consists of only one low-cost web camera which is
located directly above the center of the display screen. A five-stage algorithm is proposed to estimate the eye gaze direction. At the first stage,an efficient face detection filter based on the skin color is employed to locate the user’s face. Then three projection histograms are integrated to find the eyes. After this, the FCM algorithm is employed to locate the pupils. Then the eye gaze direction is computed by inferencing a simple fuzzy systems consisting of 9 fuzzy rules. Finally, the computed eye gaze
directions are used to manipulate the computer. Several experiments were used to test the performance of the prototype system.
關鍵字(中) ★ 人臉偵測
★ 瞳孔移動控制
★ 人眼追蹤
關鍵字(英) ★ eye tracking
★ gaze direction control
★ human face tracking
論文目次 圖目錄Ⅲ
表目錄Ⅳ
第一章介紹1
1.1研究目的1
1.2研究大綱2
第二章人臉分割4
2.1膚色切割5
2.2唇色切割9
2.3膚色投影11
2.4橢圓臉形遮罩12
2.5膚色擴張14
第三章眼睛區塊的定位17
3.1邊緣檢測的運用18
3.2亮度差值比的運用23
3.3色彩比值的運用24
3.4特徵權重26
3.5特徵重疊27
第四章瞳孔定位29
4.1二元分割的運用30
4.2以線性迴歸方程式計算人臉的側傾角以及特徵地標的設定32
4.3運用C-means 演算法求出兩眼球中心點位置34
第五章瞳孔追尋37
5.1比對技術37
5.2移動預測與錯誤識別39
第六章眼球移動控制與人機介面之應用41
6.1移動參考點的選擇以及特徵相對距離42
6.2九宮格方位判別44
6.3Fuzzy 移動控制46
6.4實驗成果49
第七章結論和展望51
第八章參考文獻52
參考文獻 [1] J. C. Wu, “人臉特徵自動抽取之演算法設計與應用,
“ URL:http://datas.ncl.edu.tw/theabs/1/, 2001.
[2] The Champion database, URL:http://www.libfind.unl.edu/alumni/
events/breakfast for champions.html.
[3] A. Kappor, “Real-time, fully automatic upper facial feature tracking,
“Proceedings of The 5th International Conference on Automatic Face
and Gesture Recognition 2002, Washington D. C, May20-21, 2002.
[4] A. M. Alattar and S. A. Rajala, “Facial Features Localization In
Front View Head and shoulders images,
“ URL:http://www.telecom.tuc.gr/paperdb/icassp99/PDF/AUTHOR/
IC992272.PDF.
[5] B. Martinkauppi, M. Laaksonen, M. Soriano, "Behavior of skin color
under varying illumination seen by different cameras at different
color spaces, " Machine Vision Applications in Industrial Inspection
IX, Martin Hunt, Editor, Proceedings of SPIE Vol. 4301 102-112,
2001.
[6] C. H. Morimoto and M. Flickner, “Real-time multiple face detection
using active illumination,” Proc. The 4th Intl. Conf. On Automatic
Face and Gesture Recognition, pp. 1-6, March 2000.
[7] C. Garcia, G. Zikos, G. Tziritas, “Face Detection in Color Images
using Wavelet Packet Analysis, “ Proceedings of the 6th IEEE
International Conference on Multimedia Computing and Systems,
Florence, pp. 703-708, 1999.
[8] G. Wyszecki and W. S. Stiles, ”Color science, ”John Wiley & Sons,
Inc, 1967.
[9] F. Du, “Human Skin Detection Using Color Segmentation,
“URL:https://courseware.vt.edu/users/abbott/5554/SkinReport.pdf
[10] H. Kashima, H. Hongo, K. Kato, and K.Yamamoto, ”A robust iris
detection method of facial and eye movement, ”Proc. Vision
Interface 2001, pp.9-14, Canada, 2001, 6.
[11] H. M. El-Bakry, “Human iris detection for information security
using fast, “ URL:http://www.wbmt.tudelft.nl.
[12] H. S. Hong, D. H. Yoo, M. J. Chung, “Real-time face tracker using
ellipse fitting and color look-up table in irregular illumination,
“ URL: http://hwrs.kaist.ac.kr/english/Sub/4/01/Newsletter/Vol3
[13] J. Tang, S. Kawato, J. Ohya, ”Face detection from a complex
background, ”Proceeding of International Workshop on Very Low
Bitrate Video Coding,Kyoto Research Park on Oct. 29-30, 1999,
JAPAN.
[14] J. C. Bezdek, “Fuzzy mathematics in pattern classification,” Ph. D
Thesis, Cornell University, 1973.
[15] J. C. Dunn, “A fuzzy relative of the ISODATA process and its use in
detecting compact, well separated clusters, “ Journal Cybern., vol. 3,
no. 3, pp. 35-57, 1973.
[16] J. M. Park, C. G. Looney, and H. C. Chen, “Fast connected
component labeling algorithm using a divide and conquer technique,
“ URL:http://cs.ua.edu/TechnicalReports/TR-2000-04.pdf.
[17] J. W. Davis, “Recognizing movement using motion histograms, ”
Technical Report No. 487, MIT Media Laboratory Perceptual
Computing Section, April 1998. 53.
[18] M. Xu, T. Akatsuka, “Detecting head pose from stereo image
sequence for active face recognition, ”AFGR98 (82-87). IEEE Top
Reference. BibRef 9800, 1998.
[19] M. Ikeda, H. Ebine and O. Nakamura, “Extraction of faces of more
than one person from natural background for personal identification,
" 2001 IEEE Canadian Conference on Electrical and Computer
Engineering, Vol. I, pp.323-328, 2001-5.
[20] N. Barrett and A. Chalmers, “Visual Stereoscopic Eye Tracking,
“URL:http://www.manukau.ac.nz/departments/e_e/research/nb.pdf
[21] R. C. K. Hua, L. C. D. Silva and P. Vadakkepat, “Detection and
tracking of faces in real environments, ” accepted to publish in the
proceedings of The 2002 International Conference on Imaging
Science, Systems, and Technology (CISST'02), to be held in Las
Vegas, USA, June 24-27, 2002
[22] R. L. Hsu, M. A. Mottaleb, and A. K. Jain, “Face detection in color
images,” IEEE Trans. Pattern Analysis and Machine Intell., 24:
696706, 2002.
[23] R. S. Feris, T. E. Campos, and R. M. Cesar, ”Detection and tracking
of facial features in video sequences, ” Proc. Mexican International
Conference on Artificial Intelligence, pages 129-137, 2000.
[24] R. Lengagne, P. Fua, and O. Monga, “3D Face Modeling from Stereo
and Differential Constraints, ” Proc. IEEE International Conference
on Automatic Face and Gesture Recognition, Nara, Japan, April
1998.
[25] S. H. Yeh, “Human facial animation based on real image sequence, ”
URL:http://sun.lib.nsysu.edu.tw/ETD-db/etd-0724101-163439.pdf,
2001.
[26] S. Baskan, M. M. Bulut and V. Atalay, “Projection based method for
segmentation of human face and its evaluation”, Pattern
Recognition Letters, Vol.23, No.14, pp. 1623-1629, 2002.
[27] S. Kawato and J. Ohya, ”Two-step approach for real-time eye
tracking with a new filtering technique, ” Proc. Int. Conf. on
System, Man & Cybernetics, pp. 1366-1371, 2000.
[28] Y. S. Chen, C. H. Su, J. H. Chen, C. S. Chen, Y. P. Hung, and C. S.
Fuh, "Video-based eye tracking for auto stereoscopic displays, "
Optical Engineering, vol. 40, no. 12, pp. 2726--2734, Dec. 2001.
[29] Y. Nakanishi, T. Fujii, K. Kiatjima, Y. Sato, H. Koike, “Vision-based
face tracking system for large displays, “ The Fourth International
Conference on Ubiquitous Computing, 2002.
[30] Z. Liposcak and S. Loncaric, “Prediction and verification for face
detection, “ Proceedings of the First Int’l Workshop on Image and
Signal Processing and Analysis, pp. 107-111, Pula, Croatia, 2000.
指導教授 蘇木春(Mu-Chun Su) 審核日期 2003-7-13
推文 facebook   plurk   twitter   funp   google   live   udn   HD   myshare   reddit   netvibes   friend   youpush   delicious   baidu   
網路書籤 Google bookmarks   del.icio.us   hemidemi   myshare   

若有論文相關問題,請聯絡國立中央大學圖書館推廣服務組 TEL:(03)422-7151轉57407,或E-mail聯絡  - 隱私權政策聲明