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論文中文名稱:基於人臉辨識之照片管理系統 [以論文名稱查詢館藏系統]
論文英文名稱:A Photo Management System Based on Face Recognition [以論文名稱查詢館藏系統]
院校名稱:臺北科技大學
學院名稱:電資學院
系所名稱:資訊工程系研究所
畢業學年度:97
出版年度:98
中文姓名:謝秉承
英文姓名:Bing-Cheng Hsieh
研究生學號:95598024
學位類別:碩士
語文別:英文
口試日期:2009-01-15
論文頁數:52
指導教授中文名:張厥煒
口試委員中文名:奚正寧;楊士萱
中文關鍵詞:照片管理人臉偵測人臉辨識
英文關鍵詞:Photo ManagementFace DetectionFace Recognition
論文中文摘要:隨著數位攝影設備的普及,個人照片的數量快速增加‧本篇論文提出一
個可以用來有效管理個人的人物照片的系統‧利用目前的人臉偵測及人臉辨
識技術,我們提供了自動及半自動的工具讓使用者可以快速連結照片和人
物‧我們對影像進行一系列針對光源變化以及不同姿勢等問題的前置處理以
提高辨識率‧我們發現在某個特定事件拍攝的個人照片中,通常只會出現一
個特定群組的人物‧我們可以根據這個特定人物群組建置人臉辨識器以簡化
問題‧我們設定了一個機制排除步不屬於這個群組的人或無法明確辨識的臉
部影像‧經過組織後的照片,會顯的較為有序並利於使用者快速排除錯誤的
辨識結果‧對於無法準確自動辨識的人臉,我們提供了一個半自動的方式,
利用提供三個可能的選項的方式讓使用從中選擇指定‧我們設計了完整的使
用者介面讓使用者可以快速進行這些動作‧針對系統的可能使用範圍,我們
進行了模擬實驗‧結果顯示當照片的數量相當龐大時,我們的系統可以大量
的減輕使用者的負擔‧
論文英文摘要:With the increasing availability of digital cameras, one can easily collect a large
number of photos. In this paper, we present a prototype system aimed to achieve
efficient management of photos of people. Using current face detection and
recognition technologies, we provide both automatic and semi-automatic methods to
facilitate the job of associating photos to people. A series of preprocessing methods
are taken to improve recognition rate for faces captured in varying lighting conditions
and poses. We found that a personal photo collection of a single event may contain
only a limited group of people. We can set up a face classifier specific for the group of
people. A threshold scheme separates people not in the group or faces that can not be
confidently identified apart. The organized result helps pick out incorrectly identified
faces. A semi-automatic approach is used to deal with the leftovers by giving three
candidates to choose from. Our proposed system is equipped with comprehensive user
interface designed for these tasks. We conducted a simulation of this usage showing
that it can dramatically reduce the amount of work on a very large set of photos.
論文目次:摘要.............................................................................................................i
Abstract........................................................................................................ii
Table of Contents .........................................................................................iii
List of Tables................................................................................................v
List of Figures ..............................................................................................vi
Chapter 1 Introduction.....................................................................................1
1.1 Research Purpose ..........................................................................1
1.2 Achievements and Limitations .......................................................1
1.3 Related Works...............................................................................3
Chapter 2 Our Photo Management System..................................................5
2.1 System Overview..........................................................................5
2.2 Maintain the Database ...................................................................7
2.3 Labeling Faces ..............................................................................9
2.4 Using Face Recognition.................................................................14
Chapter 3 Face Detector ..........................................................................16
3.1 OpenCV HAAR Detection ...........................................................16
3.2 Detector Setup...............................................................................18
3.3 Result............................................................................................19
Chapter 4 Face Classifier ..........................................................................21
4.1 Eigenface Method .........................................................................21
4.2 Training and Classifying................................................................22
4.3 Result ..........................................................................................24
Chapter 5 Face Normalization .................................................................26
5.1 Pose Normalization .......................................................................26
5.2 Image Enhancement ......................................................................28
5.3 Result............................................................................................30
Chapter 6 Simulation Results......................................................................32
6.1 Simulation 1..................................................................................32
6.2 Simulation 2..................................................................................35
Chapter 7 Conclusion and Future Works ...................................................37
References....................................................................................................39
Appendix
A User Interface ................................................................................40
A.1 Overview ...................................................................................41
iv
A.2 Entity View................................................................................41
A.2.1 Face ....................................................................................41
A.2.2 Group .................................................................................41
A.2.3 People.................................................................................43
A.2.4 Album.................................................................................45
A.2.5 Album List..........................................................................47
A.2.6 Photo ..................................................................................49
A.3 Use of GPU................................................................................51
論文參考文獻:[1] B. B. Bederson, “PhotoMesa: A Zoomable Image Browser Using Quantum Treemaps
and Bubblemaps,” In Proceedings of UIST 2001, 71–80. ACM, 2001.
[2] T. J. Mills, D. Pye, D. Sinclair, and K. R. Wood, “Shoebox: A Digital Photo Management
System,” Technical Report 2000.10, AT&T Laboratories, Cambridge, 2000.
[3] Google, Inc. Pacasa. http://picasa.google.com/
[4] A. Kuchinsky, C. Pering, M. L. Creech, D. Freeze, B. Serra, and J. Gwizdka, “FotoFile:
A Consumer Multimedia Organization and Retrieval System,” Proc. of the CHI 99 Conf.
on Human Factors in Computing Systems, pp. 496-503, 1999.
[5] Apple Computer. iPhoto. http://www.apple.com/iphoto/
[6] K. Rodden and K. R. Wood, “How Do People Manage Their Digital Photographs?” Proc.
of the SIGCHI Conf. on Human Factors in Computing Systems, pp. 409 – 416, 2003
[7] A. Girgensohn, J. Adcock, and L. Wilcox, “Leveraging Face Recognition Technology to
Find and Organize Photos,” Proc. of the 6th ACM SIGMM international workshop on
Multimedia Information Retrieval, pp. 99-106, 2004.
[8] P. Viola M. Jones, “Rapid Object Detection using a Boosted Cascade of
Simple Features,” Proc. IEEE Computer Society Conf. on Computer Vision
and Pattern Recognition, vol. 1, pp. 511-518 2001
[9] C. P. Papageorgiou, M. Oren, and T. Poggio, "A General Framework for
Object Detection," 6th Intl. Conf. on Computer Vision, 1998.
[10] M. Turk and A. Pentland, “Eigenfaces for Recognition,” J. Cognitive
Neuroscience, vol. 3, no. 1, 1991.
[11] Georgia Tech face database. http://www.anefian.com/face_reco.htm
[12] Caltech Face Database. http://www.vision.caltech.edu/html-files/archive.html
[13] S. Milborrow and F. Nicolls, “Locating Facial Features with an Extended Active
Shape Model,” ECCV, 2008.
論文全文使用權限:同意授權於2009-02-16起公開