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    政大機構典藏 > 資訊學院 > 資訊科學系 > 學位論文 >  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%.
    Reference: [1] B. Adams, C. Dorai, and S.Venkatesh, “Toward Automatic Extraction of Expressive Elements from Motion Pictures: Tempo,” IEEE Transactions on Multimedia, Vol. 4, No. 4, pp. 472-481, December 2002.
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    [17] L. Lu, H. Jiang, and H. J. Zhang, "A Robust Audio Classification and Segmentation Method," Proceedings of ACM International Conference on Multimedia, Ottawa, Ontario, Canada, pp. 203-211, September 2001.
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    [20] S. Moncrieff, C. Dorai, and S. Venkatesh, “Affect Computing in Film through Sound Energy Dynamics,” Proceedings of ACM International Conference on Multimedia, Ottawa, Ontario, Canada, pp. 525-527, September 2001.
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    [35] http://www.intel.com/technology/computing/opencv/index.htm
    [36] http://eqi.org/fw.htm
    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:[資訊科學系] 學位論文

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