i.MTV: an integrated system for mtv affective analysis

ABSTRACT

In modern time, MTV 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. It has become an significant task to develop new techniques for natural, user-friendly, and effective MTV access. In this demo, an integrated system (i.MTV) is constructed for MTV Affective Analysis, Visualization, Retrieval, and User Profile Analysis. We not only perform the effective MTV affective analysis, but also propose novel Affective Visualization techniques to make the abstract affective states intuitive and friendly to users. Based on the affective analysis and visualization, MTV affective retrieval and management are achieved. Furthermore, novel methods are proposed for user affective preferences analysis and MTV recommendation.

REFERENCES

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• 3: Giang Phuong Nguyen , Marcel Worring, Optimization of interactive visual-similarity-based search, ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP), v.4 n.1, p.1-23, January 2008 [doi>10.1145/1324287.1324294]
• 4: Xueliang Liu , Tao Mei , Xian-Sheng Hua , Bo Yang , He-Qin Zhou, Video collage, Proceedings of the 15th international conference on Multimedia, September 25-29, 2007, Augsburg, Germany [doi>10.1145/1291233.1291341]

INDEX TERMS

Primary Classification:
  I. Computing Methodologies
  I.2 ARTIFICIAL INTELLIGENCE
        I.2.10 Vision and Scene Understanding
            Subjects: Video analysis

General Terms:
Algorithms, Experimentation, Performance

Keywords:
affective content analysis, affective visualization, affinity propagation, dimensional affective model