Optimizing user expectations for video semantic filtering and abstraction

We describe a novel automatic system that generates personalized videos based on semantic filtering or summarization techniques. This system uses a new set of more than one hundred visual semantic detectors that automatically detect video concepts in faster than realtime. Based on personal profiles, the system generates either video summaries from video databases or filtered video contents from live broadcasting videos. The prototype experiments have shown the effectiveness and stabilities of the system.

[1]  Christian Timmerer,et al.  Digital item adaptation: overview of standardization and research activities , 2005, IEEE Transactions on Multimedia.

[2]  Ching-Yung Lin,et al.  ExpertiseNet: Relational and Evolutionary Expert Modeling , 2005, User Modeling.

[3]  Bernard Mérialdo,et al.  Automatic construction of personalized TV news programs , 1999, MULTIMEDIA '99.

[4]  John R. Smith,et al.  Using MPEG-7 and MPEG-21 for personalizing video , 2004, IEEE MultiMedia.

[5]  Ching-Yung Lin,et al.  Personalized video summary using visual semantic annotations and automatic speech transcriptions , 2002, 2002 IEEE Workshop on Multimedia Signal Processing..

[6]  Yong Wang,et al.  Content-adaptive utility-based video adaptation , 2003, 2003 International Conference on Multimedia and Expo. ICME '03. Proceedings (Cat. No.03TH8698).

[7]  Ching-Yung Lin,et al.  Semantic Routing and Filtering for Large-Scale Video Streams Monitoring , 2005, 2005 IEEE International Conference on Multimedia and Expo.

[8]  John Zimmerman,et al.  Content Augmentation Aspects of Personalized Entertainment Experience , 2003 .

[9]  Lie Lu,et al.  A generic framework of user attention model and its application in video summarization , 2005, IEEE Trans. Multim..

[10]  Mohammed Ghanbari,et al.  Heterogeneous Video Transcoding to Lower Spatio-Temporal Resolutions and Different Encoding Formats , 2000, IEEE Trans. Multim..

[11]  Shih-Fu Chang,et al.  Understanding and modeling user interests in consumer videos , 2004, 2004 IEEE International Conference on Multimedia and Expo (ICME) (IEEE Cat. No.04TH8763).