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Alternative TitleHorror Movie Scene Recognition Technology
Thesis Advisor胡卫明
Degree Grantor中国科学院研究生院
Place of Conferral中国科学院自动化研究所
Degree Discipline计算机应用技术
Keyword恐怖视频场景 颜色情感和颜色和谐理论 支持向量机 多示例学习 特征融合 Horror Movie Scene Color Emotion And Color Harmony Support Vector Machine Multi-instance Learning Feature Combination
Abstract网络恐怖信息过滤的研究不仅能够促进网络内容安全和人类情感认知等相关领域研究的发展,而且对构建和谐网络环境,维护社会稳定具有重要的社会意义。本文针对恐怖视频展开研究,在网络文献检索到范围内,现在几乎没有人关注恐怖视频的识别,只有在图像、视频情感分析领域的研究跟恐怖视频识别相关。要想解决恐怖视频识别问题,需要解决以下两个关键问题:(1)如何提取图像中的情感显著区域,并有效地提取与情感有关视觉特征?(2)如何有效地融合音视频的情感信息来识别恐怖视频?本文从特征层面到框架模型层面展开了一系列的研究工作。主要工作有: 1. 调研了视频结构化分析的经典算法,实现了基于信息论的帧间互信息熵的镜头分割算法。 2. 调研了大量的图像情感分析、音频情感分析的文献,提取了相关的音、视频情感特征,并把情感分析的研究成果应用到恐怖视频识别上。 3. 引入了基于心理学实验的颜色情感和颜色和谐度理论,并在这两个理论的基础上提出了一种新的具有中高层语义的颜色情感特征,实验表明我们所提出的颜色情感特征能够提高恐怖视频识别的结果。 4. 提出了基于情感认知的恐怖视频识别的框架,取得了很好的实验效果。 5. 通过对视频进行结构分析,创新性的把多示例学习方法应用到恐怖视频识别中,实验结果证明多示例学习方法很适合解决恐怖视频识别问题。 6. 构建了一个实验数据库。 总的说来,本文对恐怖视频识别作了有益的探索。
Other AbstractThe researches on horror network information filtering not only promote the development of the network content security and human emotion research in the field of cognitive, but also play an important role in building a harmonious environment and maintaining social stability. In this paper, we focus on the study of horror videos. As far as we know, there is nearly no research on the identification of horror videos before us, only image and video emotion analysis research is associated with the identification of horror video. To solve the problem of the horror video recognition, we should clear up two points as follows: (1) How to determine the salient emotion area in the image and extract the visual features with emotion? (2) How to effectively integrate audio and video emotional information to identify the horror video? We carry out series of research work from the feature level to the framework level, the main work is as follows: 1. Make a survey about video structure algorithm, and implement the method for shot boundary detection which relies on the mutual information (MI) and the joint entropy (JE) between the frames. 2. Search and research a large number of literature on image emotion analysis and audio emotion analysis, extract the relevant audio and video emotional features,furthermore introduce the results of emotion analysis into the horror video recognition. 3. Introduce the color emotion and color harmony theory based on psychological experiments and propose a new color emotional feature with the high-level semantics.Experiments show that the proposed color emotion features can improve the recognition result of horror videos. 4. Propose the framework for horror video identification based on emotional perception and achieve promising experimental results. 5. Make the structural analysis for video, then multi-instance learning is applied to horror video recognition in innovative way. Experimental results show that the multi-instance learning method is well suited to address the problem of horror video recognition. 6. Build an experimental database. In a word, in this thesis, we have made a lot of fruitful attempts and significant progresses on horror movie scene recognition.
Other Identifier200828014628014
Document Type学位论文
Recommended Citation
GB/T 7714
王建超. 电影恐怖场景识别技术[D]. 中国科学院自动化研究所. 中国科学院研究生院,2011.
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