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  1. NTU Theses and Dissertations Repository
  2. 電機資訊學院
  3. 資訊網路與多媒體研究所
請用此 Handle URI 來引用此文件: http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/10739
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dc.contributor.advisor洪一平(Yi-Ping Hung)
dc.contributor.authorWei-Ting Pengen
dc.contributor.author彭維廷zh_TW
dc.date.accessioned2021-05-20T21:54:35Z-
dc.date.available2010-08-02
dc.date.available2021-05-20T21:54:35Z-
dc.date.copyright2010-08-02
dc.date.issued2010
dc.date.submitted2010-07-27
dc.identifier.citation[1] YouTube. http://www.youtube.com/
[2] H. Zettl. Sight, sound, motion: applied media aesthetics, Wadsworth, 1998.
[3] R.M. Goodman and P. McGrath. Editing digital video : the complete creative and technical guide, McGraw-Hill/TAB Electronics, (2002).
[4] G. Chandler. Cut by cut : editing your film or video, Michael Wiese, (2006).
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[6] SONY Vegas Pro 9. http://www.sonycreativesoftware.com/vegaspro.
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[8] A. Money and H. Agius, Video summarisation: a conceptual framework and survey of the state of the art. Journal of Visual Communication and Image Representation 19, 2(2008), 121–143.
[9] P. Mulhem, M.S. Kankanhalli, H. Hassan, and J. Yi. Pivot vector space approach for audio-video mixing, IEEE Multimedia 10, 2 (2003), 28–40.
[10] J. Foote, M. Cooper, and A. Girgensohn, Creating music videos using automatic media analysis, In Proc. ACM Multimedia, (2002), 553–560.
[11] X. Hua, L. Lu, and H. Zhang, Automatic music video generation based on temporal pattern analysis, In Proc. ACM MultiMedia, (2004), 472–475.
[12] J.C. Yoon, I.K. Lee and S. Byun, Automated music video generation using multi-level feature-based segmentation, Multimedia Tools and Applications 41, 2(2009), 197–214.
[13] J. Wang , E. Chng , C.S. Xu , H.Q. Lu, and Q. Tian, Generation of personalized music sports video using multimodal cues, IEEE Transactions on Multimedia 9, 3(2007), 576–588.
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[16] W.T. Peng, W.J. Huang, W.T. Chu, C.N. Chou, W.Y. Chang, C.H. Chang, Y.P. Hung, A user experience model for home video summarization, In Proc. International Multimedia Modeling Conference, (2009), 484–495.
[17] CyberLink PowerDirector, CyberLink Corporation Inc., http://www.cyberlink.com/
[18] F. Shipman, A. Girgensohn and L. Wilcox, Authoring, viewing, and generating hypervideo: an overview of Hyper-Hitchcock, ACM Transactions on Multimedia Computing, Communications, and Applications 5, 2(2008), 1–19.
[19] MuVee AutoProducer, MuVee Technologies Pte. Ltd, http://www.muvee.com/en.
[20] W.T. Peng, Y.H. Chiang, W.T. Chu, W.J. Huang, W.L. Chang, P.C. Huang, and Y.P. Hung, Aesthetics-based automatic home video skimming system, In Proc. International Multimedia Modeling Conference, (2008), 186–197.
[21] M. Argyle, Bodily communication, Methuen & Co. Ltd, 1988.
[22] S. Sirohey, A. Rosenfeld, Eye detection in a face image using linear and nonlinear filters, Pattern Recognition 34, 7(2001), 1367–1391.
[23] T. Takagi and M. Sugeno, Fuzzy identification of systems and its applications to modeling and control, IEEE Transactions on Systems, Man and Cybernetics 15, 1(1985), 116–132.
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[25] W.Y. Chang, C.S. Chen, and Y.P. Hung, Analyzing facial expression by fusing manifolds, In Proc. Asian Conference on Computer Vision Conference, (2007), 621–630.
[26] P. Masri. “Computer modeling of sound for transformation and synthesis of musical signal,” Ph.D. dissertation, University of Bristol, UK, (1996).
[27] S. Dixon, “Onset detection revisited,” Proceedings of International Conference on Digital Audio Effects, (2006).
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[29] Yuille, A., Hallinan, P., and Cohen, D. Feature extraction from faces using deformable templates. International Journal of Computer Vision 8, 2(1992), 99–111.
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[34] R. Valenti and T. Gevers. Accurate eye center location and tracking using isophote curvature. In Proc. IEEE Computer Vision and Pattern Recognition, (2008), 1–8.
[35] M. Tűrkan, M. Pardás, and A. E. Cetin. Human eye localization using edge projection. In Proc. VISAPP, (2007), 410–415.
[36] S. Asteriadis, N. Nikolaidis, A. Hajdu, and I. Pitas. An eye detection algorithm using pixel to edge information. In Proc. Int. Symposium on Control, Communications and Signal Processing, (2006).
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[41] A. Hanjalic, “Shot-boundary detection: unraveled and resolved?” IEEE Transactions on Circuits and Systems for Video Technology 12, (2002), 90–105.
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dc.identifier.urihttp://tdr.lib.ntu.edu.tw/jspui/handle/123456789/10739-
dc.description.abstract本論文目的是讓一般家庭使用者在最輕鬆的情況下,輸入他所拍攝的家庭影片以及一段他喜歡的音樂,系統就會自動結合此段影片與音樂並生成一段有節奏性的MV(Music Video)。與以往的自動生成影片系統相比,本系統的特色在於使用一些剪接理論與美學的觀念,並且將其轉化成可行之演算法。此外,我們也加入心理學方面的研究,嚐試從使用者在觀賞影片時的生理反應,包括眼睛運動與表情,作為我們標記每段影片重要性的依據,並將其分析的數據轉成影片摘要的結果。最後將系統進一步用UI來呈現,嚐試讓使用者可以參與修改電腦最後分析的結果。也加入與以往商用剪接軟體不同的操作想法,企圖在剪接表現上創造不同的可能。zh_TW
dc.description.abstractIn this dissertation, we propose a novel home video editing system for generating music videos (MV) based on rhythmic control and the user interests. With the aid of rhythmic control from editing theories, the developed system is able to generate appealing and rhythmic music videos. We construct a module called “Interest Meter” to analyze variations of viewer’s blink rate, eye movement and facial expression when s/he watches unorganized raw home videos. This system transforms user’s behaviors into clues for determining important parts of video shots. Moreover, the friendly user interface allows novices to efficiently edit videos without difficulty. Experimental results show that this new editing mechanism can effectively generate music video summaries and can greatly reduce efforts of manual editing.en
dc.description.provenanceMade available in DSpace on 2021-05-20T21:54:35Z (GMT). No. of bitstreams: 1
ntu-99-D93944004-1.pdf: 1994578 bytes, checksum: d98a5deb6eee285c886c4c158d041607 (MD5)
Previous issue date: 2010
en
dc.description.tableofcontents1. Introduction 1
2. Related Work 3
2.1 From the perspective of information analysis 3
2.2 From the perspective of audio-visual synthesis 5
2.3 From the perspective of computer-human interaction 5
2.4 Contributions of our system 6
3. Observation and Inquiry 8
3.1 Observation 1: Characteristic of Music Video 8
3.2 Observation 2: Difficulty of Music Video Editing 10
3.2.1 Establishing Video Rhythm is Difficult 10
3.2.2 Repeat Cutting is Time Consuming Work 10
4. System Framework 12
4.1 Video and Music Analysis 12
4.2 Interest Meter 13
4.3 User Interface 13
5. Video and Music Analysis 14
5.1 Video analysis 14
5.2 Music analysis 19
6. Interest Meter 21
6.1 Attention Model 22
6.1.1 Head Motion Detection and Score Calculation 22
6.1.2 Blinking and Saccade Detection 22
6.1.3 Blinking Score Calculation 26
6.1.4 Saccade Score Calculation 26
6.1.5 Attention Score Calculation 26
6.2 Emotion Model 28
6.2.1 Facial Expression Recognition 28
6.2.2 Emotion Score Calculation 29
6.2.3 Interest Score Computing and Weighting Adjustment 30
7. Summary Generation 32
7.1 Rhythm Establishment 32
7.2 Shot Trimming 34
7.3 Transition Determination 35
8. User Interface 37
8.1 Video Editing 37
8.1 Rhythmic Control 39
9. Experimental Results 41
9.1 Quality Estimation 42
9.2 Evaluation of Interest Meter 43
9.2.1 Accuracy of Iris Center Location 43
9.2.2 Accuracy of Facial Expression Recognition 45
9.2.3 Verification of Interest Meter 46
9.3 User Study on Interface 47
9.4 Experiments 1 on Summarization 52
9.5 Experiments 2 on Summarization 54
9.5.1 Procedure 55
9.5.2 Results and Discussion 56
10. Conclusions and Future Work 58
11. Bibliography 60
dc.language.isoen
dc.title基於使用者興趣量表與節奏控制的家庭音樂影片剪輯系統zh_TW
dc.titleMV-Style Home Video Editing System Based on User Interests and Rhythmic Controlen
dc.typeThesis
dc.date.schoolyear98-2
dc.description.degree博士
dc.contributor.oralexamcommittee鄭士康(Shyh-Kang Jeng),范國清(Kuo-Chin Fan),莊仁輝(Jen-Hui Chuang),黃仲陵(Chung-Lin Huang),林嘉文(Chia-Wen Lin),莊永裕(Yung-Yu Chuang),徐宏民(Winston H. Hsu)
dc.subject.keyword興趣量表,媒體美學,影片摘要,臉部表情,眼球運動,zh_TW
dc.subject.keywordInterest meter,media aesthetics,video summarization,facial expression,eye movement,en
dc.relation.page63
dc.rights.note同意授權(全球公開)
dc.date.accepted2010-07-27
dc.contributor.author-college電機資訊學院zh_TW
dc.contributor.author-dept資訊網路與多媒體研究所zh_TW
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