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Affective Visualization and Retrieval for Music Video

Affective Visualization and Retrieval for Music Video,10.1109/TMM.2010.2059634,IEEE Transactions on Multimedia,Shiliang Zhang,Qingming Huang,Shuqiang

Affective Visualization and Retrieval for Music Video   (Citations: 3)
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In modern times, music video (MV) has become an important favorite pastime to people because of its conciseness, convenience, and the ability to bring both audio and visual experiences to audiences. As the amount of MVs is explosively increasing, it has become an important task to develop new techniques for effective MV analysis, retrieval, and management. By stimulating the human affective response mechanism, affective video content analysis extracts the affective information contained in videos, and, with the affective information, natural, user-friendly, and effective MV access strategies could be developed. In this paper, a novel integrated system (i.MV) is proposed for personalized MV affective analysis, visualization, and retrieval. In i.MV, we not only perform the personalized MV affective analysis, which is a challenging and insufficiently covered problem in current affective content analysis field, but also propose novel affective visualization to convert the abstract affective states intuitive and friendly to users. Based on the affective analysis and visualization, affective information based MV retrieval is achieved. Both comprehensive experiments and subjective user studies on a large MV dataset demonstrate that our personalized affective analysis is more effective than the previous algorithms. In addition, affective visualization is proved to be more suitable for affective information-based MV retrieval than the commonly used affective state representation strategies.
Journal: IEEE Transactions on Multimedia - TMM , vol. 12, no. 6, pp. 510-522, 2010
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    • ...All the current affective analysis systems try to solve the following problems [83]: 1) identification of valid affective features; 2) bridging the gap between affective features and affective states; 3) establishing an affective model to take user’s personality into consideration; 4) representing affective state...

    Yijuan Luet al. Personalization in multimedia retrieval: A survey

    • ...Most previous and existing works on affective video classification focus on detecting video affective content by using low-level features [2, 3, 4, 5, 6]. In [2], HMMs were used to categorize videos into three types of affective content, fear, sadness and joy, based on low-level visual features...
    • ...In [6], arousal and valence features are extracted to implement an integrated system for personalized music video affective analysis, visualization, and retrieval...

    Sicheng Zhaoet al. Affective Video Classification Based on Spatio-temporal Feature Fusion

    • ...User’s emotion can be recognized and expressed, document [6] has researched in the affective visualization, document [7] has built affective model for emotion...

    Quan Luet al. A User Model for Recommendation Based on Facial Expression Recognition

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