2000 IEEE International Conference on Multimedia and Expo. ICME2000. Proceedings. Latest Advances in the Fast Changing World of Multimedia (Cat. No.00TH8532)
ACM Transactions on Intelligent Systems and Technology, 2013
Multimedia data on social websites contain rich semantics and are often accompanied with user-def... more Multimedia data on social websites contain rich semantics and are often accompanied with user-defined tags. To enhance Web media semantic concept retrieval, the fusion of tag-based and content-based models can be used, though it is very challenging. In this article, a novel semantic concept retrieval framework that incorporates tag removal and model fusion is proposed to tackle such a challenge. Tags with useful information can facilitate media search, but they are often imprecise, which makes it important to apply noisy tag removal (by deleting uncorrelated tags) to improve the performance of semantic concept retrieval. Therefore, a multiple correspondence analysis (MCA)-based tag removal algorithm is proposed, which utilizes MCA's ability to capture the relationships among nominal features and identify representative and discriminative tags holding strong correlations with the target semantic concepts. To further improve the retrieval performance, a novel model fusion method i...
Fourth International Conference on Information, Communications and Signal Processing, 2003 and the Fourth Pacific Rim Conference on Multimedia. Proceedings of the 2003 Joint
International Journal of Software Engineering and Knowledge Engineering, 2010
Natural disasters, such as hurricanes, have had an enormous social and economical impact on socie... more Natural disasters, such as hurricanes, have had an enormous social and economical impact on society in the United State and around the world for many years. With the goal of preventing, diverting, or weakening the destructive forces of tropical cyclones, the preparedness of the public plays a major role in the magnitude of inflicted damage due to these storms. Acknowledging the captivating power of social networking and Web 2.0 over society, we present a prototype system which integrates meteorological data along with user generated content with the aim of improving public response by increasing their situational awareness due to such natural threats. The proposed system aggregates storm track and wind analysis data from the existing H*Wind system along with videos taken from YouTube and presents it to the user in Google Earth. A content-based concept detection mechanism is used to evaluate the relevance of the extracted YouTube videos to the storm of interest. The proposed system demonstrates the potential public benefit resulting from the integration of the areas of multimedia content analysis, Web 2.0, and meteorology.
The analysis and mining of traffic video sequences to discover important but previously unknown k... more The analysis and mining of traffic video sequences to discover important but previously unknown knowledge such as vehicle identification, traffic flow, queue detection, incident detection, and the spatio-temporal relations of the vehicles at intersections, provide an economic approach for daily traffic monitoring operations. To meet such demands, a multimedia data mining framework is proposed in this paper. The proposed multimedia
2000 IEEE International Conference on Multimedia and Expo. ICME2000. Proceedings. Latest Advances in the Fast Changing World of Multimedia (Cat. No.00TH8532)
ACM Transactions on Intelligent Systems and Technology, 2013
Multimedia data on social websites contain rich semantics and are often accompanied with user-def... more Multimedia data on social websites contain rich semantics and are often accompanied with user-defined tags. To enhance Web media semantic concept retrieval, the fusion of tag-based and content-based models can be used, though it is very challenging. In this article, a novel semantic concept retrieval framework that incorporates tag removal and model fusion is proposed to tackle such a challenge. Tags with useful information can facilitate media search, but they are often imprecise, which makes it important to apply noisy tag removal (by deleting uncorrelated tags) to improve the performance of semantic concept retrieval. Therefore, a multiple correspondence analysis (MCA)-based tag removal algorithm is proposed, which utilizes MCA's ability to capture the relationships among nominal features and identify representative and discriminative tags holding strong correlations with the target semantic concepts. To further improve the retrieval performance, a novel model fusion method i...
Fourth International Conference on Information, Communications and Signal Processing, 2003 and the Fourth Pacific Rim Conference on Multimedia. Proceedings of the 2003 Joint
International Journal of Software Engineering and Knowledge Engineering, 2010
Natural disasters, such as hurricanes, have had an enormous social and economical impact on socie... more Natural disasters, such as hurricanes, have had an enormous social and economical impact on society in the United State and around the world for many years. With the goal of preventing, diverting, or weakening the destructive forces of tropical cyclones, the preparedness of the public plays a major role in the magnitude of inflicted damage due to these storms. Acknowledging the captivating power of social networking and Web 2.0 over society, we present a prototype system which integrates meteorological data along with user generated content with the aim of improving public response by increasing their situational awareness due to such natural threats. The proposed system aggregates storm track and wind analysis data from the existing H*Wind system along with videos taken from YouTube and presents it to the user in Google Earth. A content-based concept detection mechanism is used to evaluate the relevance of the extracted YouTube videos to the storm of interest. The proposed system demonstrates the potential public benefit resulting from the integration of the areas of multimedia content analysis, Web 2.0, and meteorology.
The analysis and mining of traffic video sequences to discover important but previously unknown k... more The analysis and mining of traffic video sequences to discover important but previously unknown knowledge such as vehicle identification, traffic flow, queue detection, incident detection, and the spatio-temporal relations of the vehicles at intersections, provide an economic approach for daily traffic monitoring operations. To meet such demands, a multimedia data mining framework is proposed in this paper. The proposed multimedia
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Papers by Mei-Ling Shyu