政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/38537

政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/38537

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政大典藏 > College of Informatics > Department of Computer Science > Theses > Item 140.119/38537

Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/38537

Title:	基於電影拍攝手法之電影場景情緒探勘 Emotion Discovery of Movie Content Based on Film Grammar
Authors:	廖家慧 Liao, Chia Hui
Contributors:	沈錳坤 Shan, Man Kwan 廖家慧 Liao, Chia Hui
Keywords:	內涵式分析拍攝手法電影場景視聽覺特徵情緒 content-based analysis film grammar movie scene audiovisual features emotion affective classification
Date:	2007
Issue Date:	2010-04-09 13:17:50 (UTC+8)
Abstract:	數位化的今天，電影逐漸成為人們日常生活的一部份，電影資料的內涵式分析也成為目前重要的研究主題。透過電影拍攝手法，我們知道電影視聽覺特徵與情緒之間有密不可分的關係。因此，在本研究中，我們希望利用探勘電影視聽覺特徵與情緒的關聯來達到自動判斷電影場景的情緒。首先，先由人工標記訓練場景的情緒，之後，我們對所有的場景擷取定義的六類特徵值。特徵值包括電影場景的顏色、燈光、影片速度、特寫鏡頭、聲音和字幕六類。最後，我們利用Mixed Media Graph演算法來探勘場景情緒與特徵值之間的關聯，達到自動判斷電影場景情緒的功能。實驗結果顯示，準確率最高可達到70%。 Movies play an important role in our life nowadays. How to analyze the emotional content of movies becomes one of the major issues. Based on film grammar, there are many audiovisual cues in movies helpful for detecting the emotions of scenes. In this research, we investigate the discovery of the relationship between audiovisual cues and emotions of scenes and the automatic emotion annotation of scenes is achieved. First, the training scenes are labeled with the emotions manually. Second, six classes of audiovisual features are extracted from all scenes. These classes of features consist of color, light, tempo, close-up, audio, and textual. Finally, the graph-based approach, Mixed Media Graph is modified to mine the association between audiovisual features and emotions of the scenes. The experiments show that the accuracy achieves 70%.
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Saunders, “Real-Time Discrimination of Broadcast Speech/Music,” Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP ’96), Atlanta, Ga, Vol. 2, pp. 993-996, May 1996. [30] E. Scheirer and M. Slaney, “Construction and Evaluation of a Robust Multifeature Speech/Music Discriminator”, Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP ’97), Munich, Germany, Vol. 2, pp. 1331-1334, April 1997. [31] R. E. Thayer, The Biopsychology of Mood and Arousal. New York: Oxford University Press, 1989. [32] H. L. Wang and L. F. Cheong, “Affective Understanding in Film,” IEEE Transactions on Circuits and Systems for Video Technology (CSVT), Vol. 16, No. 6, pp. 689-704, June 2006. [33] C. Y. Wei, N. Dimitrova, and S.F. Chang, “Color-Mood Analysis of Films on Syntactic and Psychological Models,” Proceedings of IEEE International Conference on Multimedia and Expo. (ICME ’04), Taipei, Taiwan, pp. 831-834, June 2004. 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Description:	碩士國立政治大學資訊科學學系 94753027 96
Source URI:	http://thesis.lib.nccu.edu.tw/record/#G0094753027
Data Type:	thesis
Appears in Collections:	[Department of Computer Science ] Theses

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