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研究生:吳玉善
研究生(外文):Yu-Shan Wu
論文名稱:非監督式主播影像偵測於新聞故事分段之研究
論文名稱(外文):The Study of Unsupervised Anchorperson Image Detection for News Story Segmentation
指導教授:傅心家傅心家引用關係
指導教授(外文):Hsin-Chia Fu
學位類別:碩士
校院名稱:國立交通大學
系所名稱:資訊科學與工程研究所
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2007
畢業學年度:95
語文別:中文
論文頁數:47
中文關鍵詞:人臉偵測分群新聞故事
外文關鍵詞:Face DetectionClusteringNews Story
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建立一個全自動的新聞故事分段系統是一個重要且富挑戰性的工作。一則新聞故事段落是由主播播報與外景採訪所組成,所以若能夠知道主播出現的時段就能將一個連續的新聞影片自動分段。本篇論文提出一個以偵測人臉為基礎的主播偵測方式。首先偵測每張新聞影像的人臉區域,利用人臉區域取出特徵,以此特徵做分群,假設最大群是主播,進而篩選出主播人臉區域。因為只注意影像中有人臉的區域,不會受到複雜背景的影響,沒有偵測鏡頭轉換的問題;還有在判斷那張影像有主播的過程並沒有使用主播影像模型,所以不需要為了每個主播去調整模型。我們以5個小時不同電視台的整點新聞影片進行主播影像偵測與新聞故事切割的實驗,驗證所提的方法能正確的找出主播出現的時段。論文最後更進一步將所提的方法整合至一個已有的新聞系統中並成功的應用在東森晚間新聞故事的切割上。
Building an automatic system for news story segmentation is an important and challenging task. A news story is composed of an anchorperson shot and a news footage shot, we can segment a news video into several stories if we know when the anchorperson shows up. This paper presents a method for anchorperson detection based on face detection. First, detecting human faces region in every news frame. Then, extracting features by the face region, and clustering on all features. Suppose that the biggest cluster is presented for anchorperson。This method would not effected by the complex background because it focuses only on the face region. And because of its unsupervised nature, the algorithm does not need to adjust model for different anchorpersons. The efficacy of the proposed method is tested on 5 h of news programs. Moreover, we integrate
the proposed method to an existed news video library system and segmenting on the ETT news programs successfully.
摘要................................................................i
Abstract............................................................ii
誌謝..............................................................iii
目錄...............................................................iv
表目錄.............................................................vi
圖目錄............................................................vii
第一章 前言........................................................1
1.1 研究動機...................................................1
1.2 研究目標...................................................1
1.3 研究方向...................................................2
1.4 章節介紹...................................................3
第二章 人臉偵測之相關研究..........................................4
2.1 由上而下的以知識為基礎的方法................................4
2.2 由下而上的以特徵為基礎的方法................................5
2.3 樣板比對方法................................................8
2.4 以表面跡象為基礎的方法......................................9
第三章 主播影像偵測與新聞故事切割.................................13
3.1 人臉區塊偵測與追蹤.........................................15
3.1.1 人臉偵測...............................................16
3.1.2 以人臉追蹤來加速人臉偵測...............................23
3.2 主播人臉區塊篩選...........................................26
3.2.1 根據人臉區塊的特性抽取特徵.............................26
3.2.2 基於最大群原則的主播區域篩選...........................27
3.3 新聞故事切割...............................................28
第四章 實驗結果...................................................29
4.1 主播影像偵測實驗與結果分析................................29
4.1.1 人臉偵測實驗與結果分析................................30
4.1.2 分群實驗與結果分析....................................32
4.2 新聞故事切割實驗與結果分析................................38
4.3 新聞故事切割系統應用與結果分析............................40
第五章 結論與未來展望.............................................43
5.1 結論......................................................43
5.2 未來展望..................................................43
參考文獻...........................................................45
【1】 Xinbo Gao and Xiaoou Tang, “Unsupervised Video-Shot Segmentation and Model-Free Anchorperson Detection for News Video Story Parsing ,” IEEE Trans. Circuits and System for Video Technology, pp.756-776,Sep. 2002

【2】 鄭士賢, “Model-based learning for Gaussian Mixture Model and its application on Speaker Identification,” 國立交通大學,資訊工程研究所碩士論文, 民國九十一年

【3】 Ming-Hsuan Yang, David J. Kriegman and Narendra Ahuja, “Detecting Faces in Images: A Survey,” IEEE Tran. Pattern Analysis and Machine Intelligence, vol. 24, Issue 1, pp. 34-58,Jan. 2002

【4】 C. Kotropoulos and I. Pitas, “Rule-Based Face Detection in Frontal Views,” Proc. Int’l Conf. Acoustics, Speech and Signal Processing, vol. 4, pp. 2537-2540, 1997

【5】 H.P. Graf, T. Chen, E. Petajan and E. Cosatto, “Locating Faces and Facial Parts,” Proc. First Int’l. Workshop Automatic Face and Gesture Recognition, pp. 41-46, 1995

【6】 T.S. Jebara and A. Pentland, “Parameterized Structure from Motion for 3D Adaptive Feedback Tracking of Faces,” Proc. IEEE Conf. Computer Vision and Pattern Recognition, pp. 144-150. 1997

【7】 H. Wang and S.-F. of Chang, “A Highly Efficient System for Automatic Face Region Detection in MPEG Video,” IEEE Trans. Circuits and System for Video Technology, vol. 7, no. 4, pp. 615-628, 1997

【8】 D. Saxe and R. Foulds, “Toward Robust Skin Identification in Video Images,” Proc. Second Int’l Conf. Automatic Face and Gesture Recognition, pp. 379-384, 1996

【9】 Y. Dai and Y. Nakano, “Extraction for Facial Images from Complex Background Using Color Information and SGLD Matrices,” Proc.IEEE Conf. Computer Vision & Image Processing, vol. 1, pp. 137-141 Oct 1994

【10】 M.-H. Yang and N.Ahuja, “Detecting Human Faces in Color
Images,” Proc. IEEE int’l Conf. Image Processing, vol. 1, pp.
127-130, 1998

【11】 D. Chai and K.N. Ngan, “Locating Facial Region of a
Head-and-Shoulders Color Images,” Proc. Third Int’l Conf.
Automatic Face and Gesture Recognition, pp. 124-129, 1998

【12】 J.L. Crowley and J.M. Bedrune, “Integration and Control of
Reactive Visual Processes,” Proc. Third European Conf. Computer
Vision, Vol. 2, pp. 47-58, 1994

【13】 I. Cai, A. Goshtasby and C. Yu, “Detecting Human Faces in Color
Images,” Proc. 1998 Int’l Workshop Multi-Media Database
Management Systems, pp. 124-131, 1998

【14】 陳鍛生和劉政凱, “膚色檢測技術綜述,”計算機學報, Chinese
Journal of Computers, 02期, 2006

【15】 Michael J.Jones and James M.Rehg, “Statistical Color Models with
Application to Skin Detection,” IEEE Computer Society
Conference, Computer Vision and Pattern Recognition, vol. 1, pp,
23-25. June, 1999

【16】 Tze-Yin Chow, Kin-Man Lam and Kwok-Wai Wong, “Efficient color
face detection algorithm under different lighting conditions,” Journal of Electronic Imaging, vol 15, pp. Jan, 2006

【17】 Dorin Comaniciu and Peter Meer, “Mean Shift: A Robust Approach
Toward Feature Space Analysis,” IEEE Trans Pattern Analysis and
Machine Intelligence, vol. 24, Issue. 5, pp, 603-619. May, 2002

【18】 D. Chetverikov and A. Lerch, “Multiresolution Face Detection,”
Theoretical Foundations of Computer Vision, vol. 69, pp. 131-140,
1993

【19】 C.-C. Han, H.-Y.M. Liao, K.-C. Yu and L.-H. Chen, “Fast Face
Detection via Morphology-Based Pre-Processing,” Proc. Ninth
Int’l Conf. Image Analysis and Processing, pp. 469-476, 1998

【20】 T. Sakai, M. Nagao and S. Fujibayashi, “Line Extraction and
Pattern Detection in a Photograph,” Pattern Recognition, vol.
1, pp. 233-248, 1969

【21】 P. Sinha, “Object Recognition via Image Invariants: A Case
Study,” Investigation Ophthalmology and Visual Science, vol.
35, no. 4, pp. 1735-1740, 1994

【22】 J. Miao, B. Yin, K. Wang, L. Shen and X. Chen, “A Hierarchical
Multiscale and Multiangle System for Human Face Detection in
Complex Background Using Gravity-Center Template,” Pattern
Recognition, vol. 32, no. 7, pp. 1237-1248, 1999

【23】 M. Turk and A. Pentland, “Eigenfaces for Recognition,”
J.Cognitive Neuroscience, vol. 141, pp. 245-250, 1991

【24】 H. Rowley, S. Baluja and T. Kanade, “Neural Network-Based Face
Detection,”IEEE Trans. Pattern Analysis and Machine
Intelligence, vol. 20, no.1, pp. 23-38, Jan. 1998

【25】 E. Osuna, R. Freund and F. Girosi, “Training Support Vector
Machines: An Application to Face Detection,” Proc. IEEE Conf.
Computer Vision and Pattern Recognition, pp. 130-136, 1997

【26】 K-K. Sung and T. Poggio, “Example-Based Learning for View-Based
Human Face Detection,” IEEE Trans. Pattern Analysis and Machine
Intelligence, vol. 20, no. 1, pp. 39-51, Jan. 1998
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