| Project/Area Number |
17500073
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Media informatics/Database
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| Research Institution | Iwate Prefectural University |
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Principal Investigator |
ITOH Yoshiaki Iwate Prefectural University, Faculty of Software and Information Science, Associate professor (90325928)
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| Co-Investigator(Kenkyū-buntansha) |
OKAWA Shigeki Chiba Institute University, Faculty of Software and Information Science, Associate professor (40306395)
KOJIMA Kazunori Iwate Prefectural University, Faculty of Software and Information Science, Research associate (60305307)
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| Project Period (FY) |
2005 – 2007
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| Project Status |
Completed (Fiscal Year 2007)
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| Budget Amount *help |
¥3,770,000 (Direct Cost: ¥3,500,000、Indirect Cost: ¥270,000)
Fiscal Year 2007: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2006: ¥1,100,000 (Direct Cost: ¥1,100,000)
Fiscal Year 2005: ¥1,500,000 (Direct Cost: ¥1,500,000)
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| Keywords | retrieval / video data / structure / segmentation / music retrieval / music information / acoustic feature / 音声検索 / 音楽情報処理 / 音声特徴量 / 音楽特徴量 |
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| Research Abstract |
The first theme of this research is to realize an automatic video segmentation. For this purpose,we developed the methods for extracting a local and global feature of video information and for classifying video data sets. The second theme is automatic extraction of the structure for segmented video data sets using local and global similarity and dissimilarity between the segmented sections. This research first conducted the analysis of local acoustic and image similarity in video data sets,and extracted similar partial sections that are repeated in a music piece. The developed method then discriminated speech sections and music sections respectively using a local feature and a global feature.We confirmed the developed methods worked well for real video data sets. The research also conducted speech retrieval by a text and speech query for speech video sections segmented by the above method. For speech retrieval,new technique of dealing with any words for a query and the integration method for plural subword models were proposed,and the experimental results demonstrated the method showed better performance compared to former methods. These results were reported at the many domestic and international conferences. In the future,we are going to develop the methods for the actual use.
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