A web community-based video retrieval method using canonical correlation analysis

Authors:
Yasutaka Hatakeyama;Takahiro Ogawa;Satoshi Asamizu;Miki Haseyama
Affiliations:
Graduate School of Information Science and Technology, Hokkaido University, Sapporo, Japan;Graduate School of Information Science and Technology, Hokkaido University, Sapporo, Japan;Kushiro National College of Technology, Kushiro, Japan;Graduate School of Information Science and Technology, Hokkaido University, Sapporo, Japan
Venue:
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Year:
2009

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Abstract

This paper presents a Web community-based video retrieval method using canonical correlation analysis (CCA). In the proposed method, two novel approaches are introduced into the retrieval scheme of video materials on the Web. First, the CCA is applied to three kinds of video features, visual and audio features of video materials and textual features obtained fromWeb pages containing those video materials. This approach provides a solution of problems of traditional methods of not being able to calculate similarities between different kinds of video features. Furthermore, from the obtained similarities and link relationships of Web pages, a new adjacency matrix is defined, and link analysis can be applied to this matrix. Then, the Web communities of the video materials whose topics are similar to each other can be automatically extracted based on their features. Therefore, by ranking the video materials in the obtained Web community, accurate video retrieval can be realized.