Automatic Detection of Video Shot Boundary in Social Media Using a Hybrid Approach of HLFPN and Keypoint Matching
Shot boundary detection (SBD) is an important and fundamental step in video content analysis such as content-based video indexing, browsing, and retrieval. In this paper, a hybrid SBD method is presented by integrating a high-level fuzzy Petri net (HLFPN) model with keypoint matching. The HLFPN mode...
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| Veröffentlicht in: | IEEE transactions on computational social systems 2018-03, Vol.5 (1), p.210-219 |
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| container_title | IEEE transactions on computational social systems |
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| creator | Rong-Kuan Shen Yi-Nan Lin Juang, Tony Tong-Ying Shen, Victor R. L. Soo Yong Lim |
| description | Shot boundary detection (SBD) is an important and fundamental step in video content analysis such as content-based video indexing, browsing, and retrieval. In this paper, a hybrid SBD method is presented by integrating a high-level fuzzy Petri net (HLFPN) model with keypoint matching. The HLFPN model with histogram difference is executed as a predetection. Next, the speeded-up robust features (SURF) algorithm that is reliably robust to image affine transformation and illumination variation is used to figure out all possible false shots and the gradual transition based on the assumption from the HLFPN model. The top-down design can effectively lower down the computational complexity of SURF algorithm. The proposed approach has increased the precision of SBD and can be applied in different types of videos. |
| doi_str_mv | 10.1109/TCSS.2017.2780882 |
| format | Article |
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L.</creatorcontrib><creatorcontrib>Soo Yong Lim</creatorcontrib><title>Automatic Detection of Video Shot Boundary in Social Media Using a Hybrid Approach of HLFPN and Keypoint Matching</title><title>IEEE transactions on computational social systems</title><addtitle>TCSS</addtitle><description>Shot boundary detection (SBD) is an important and fundamental step in video content analysis such as content-based video indexing, browsing, and retrieval. In this paper, a hybrid SBD method is presented by integrating a high-level fuzzy Petri net (HLFPN) model with keypoint matching. The HLFPN model with histogram difference is executed as a predetection. Next, the speeded-up robust features (SURF) algorithm that is reliably robust to image affine transformation and illumination variation is used to figure out all possible false shots and the gradual transition based on the assumption from the HLFPN model. The top-down design can effectively lower down the computational complexity of SURF algorithm. The proposed approach has increased the precision of SBD and can be applied in different types of videos.</description><subject>Algorithm design and analysis</subject><subject>Cameras</subject><subject>Computational modeling</subject><subject>High-level fuzzy Petri net (HLFPN)</subject><subject>Histograms</subject><subject>keypoint matching</subject><subject>Petri nets</subject><subject>Robustness</subject><subject>shot boundary detection (SBD)</subject><subject>speeded-up robust features (SURF)</subject><issn>2329-924X</issn><issn>2329-924X</issn><issn>2373-7476</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNpNkNFOwjAUhhujiQR5AOPNeYFh263teokozAhqMjDeLaVrpQbWuZUL3t4tEOPVf5L_fCc5H0K3BI8JwfJ-Nc3zMcVEjKlIcZrSCzSgMZWRpMnn5b_5Go3a9htjTChjguIB-pkcgt-r4DQ8mmB0cL4Cb-HDlcZDvvUBHvyhKlVzBFdB7rVTO1ia0ilYt676AgXZcdO4EiZ13Xiltz2eLWbvr6CqEl7MsfauCrBUQW874AZdWbVrzeicQ7SePa2mWbR4mz9PJ4tIU85CVEpmGTOWJJJxmXJBhIpTnsiYE0ysjZlgVmAqNOacdWEx18mm6zfcWsLjISKnu7rxbdsYW9SN23d_FAQXvbai11b02oqzto65OzHOGPO33xWSJyL-BUqrZ9M</recordid><startdate>201803</startdate><enddate>201803</enddate><creator>Rong-Kuan Shen</creator><creator>Yi-Nan Lin</creator><creator>Juang, Tony Tong-Ying</creator><creator>Shen, Victor R. 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L.</creatorcontrib><creatorcontrib>Soo Yong Lim</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Electronic Library (IEL)</collection><collection>CrossRef</collection><jtitle>IEEE transactions on computational social systems</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Rong-Kuan Shen</au><au>Yi-Nan Lin</au><au>Juang, Tony Tong-Ying</au><au>Shen, Victor R. L.</au><au>Soo Yong Lim</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Automatic Detection of Video Shot Boundary in Social Media Using a Hybrid Approach of HLFPN and Keypoint Matching</atitle><jtitle>IEEE transactions on computational social systems</jtitle><stitle>TCSS</stitle><date>2018-03</date><risdate>2018</risdate><volume>5</volume><issue>1</issue><spage>210</spage><epage>219</epage><pages>210-219</pages><issn>2329-924X</issn><eissn>2329-924X</eissn><eissn>2373-7476</eissn><coden>ITCSGL</coden><abstract>Shot boundary detection (SBD) is an important and fundamental step in video content analysis such as content-based video indexing, browsing, and retrieval. In this paper, a hybrid SBD method is presented by integrating a high-level fuzzy Petri net (HLFPN) model with keypoint matching. The HLFPN model with histogram difference is executed as a predetection. Next, the speeded-up robust features (SURF) algorithm that is reliably robust to image affine transformation and illumination variation is used to figure out all possible false shots and the gradual transition based on the assumption from the HLFPN model. The top-down design can effectively lower down the computational complexity of SURF algorithm. The proposed approach has increased the precision of SBD and can be applied in different types of videos.</abstract><pub>IEEE</pub><doi>10.1109/TCSS.2017.2780882</doi><tpages>10</tpages><orcidid>https://orcid.org/0000-0001-8194-3446</orcidid></addata></record> |
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| ispartof | IEEE transactions on computational social systems, 2018-03, Vol.5 (1), p.210-219 |
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| language | eng |
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| source | IEEE Electronic Library (IEL) |
| subjects | Algorithm design and analysis Cameras Computational modeling High-level fuzzy Petri net (HLFPN) Histograms keypoint matching Petri nets Robustness shot boundary detection (SBD) speeded-up robust features (SURF) |
| title | Automatic Detection of Video Shot Boundary in Social Media Using a Hybrid Approach of HLFPN and Keypoint Matching |
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