Automatic recognition of film genres
Proceedings of the third ACM international conference on Multimedia
Media Computing: Computational Media Aesthetics
Media Computing: Computational Media Aesthetics
Pattern Recognition and Image Preprocessing
Pattern Recognition and Image Preprocessing
Audio-Visual Event Detection using Duration dependent input output Markov models
CBAIVL '01 Proceedings of the IEEE Workshop on Content-based Access of Image and Video Libraries (CBAIVL'01)
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
Automated extraction of music snippets
MULTIMEDIA '03 Proceedings of the eleventh ACM international conference on Multimedia
Multimedia semantic indexing using model vectors
ICME '03 Proceedings of the 2003 International Conference on Multimedia and Expo - Volume 1
Horror film genre typing and scene labeling via audio analysis
ICME '03 Proceedings of the 2003 International Conference on Multimedia and Expo - Volume 1
Highlight sound effects detection in audio stream
ICME '03 Proceedings of the 2003 International Conference on Multimedia and Expo - Volume 3 (ICME '03) - Volume 03
Shot-boundary detection: unraveled and resolved?
IEEE Transactions on Circuits and Systems for Video Technology
A comparison of methods for multiclass support vector machines
IEEE Transactions on Neural Networks
Extracting semantics from audio-visual content: the final frontier in multimedia retrieval
IEEE Transactions on Neural Networks
Tactile and visual alerts for deaf people by mobile phones
Proceedings of the 11th international ACM SIGACCESS conference on Computers and accessibility
ICME'09 Proceedings of the 2009 IEEE international conference on Multimedia and Expo
The design of human-powered access technology
The proceedings of the 13th international ACM SIGACCESS conference on Computers and accessibility
A context aware sound classifier applied to prawn feed monitoring and energy disaggregation
Knowledge-Based Systems
Hi-index | 0.00 |
Semantic-level content analysis is a crucial issue in achieving efficient content retrieval and management. We propose a hierarchical approach that models audio events over a time series in order to accomplish semantic context detection. Two levels of modeling, audio event and semantic context modeling, are devised to bridge the gap between physical audio features and semantic concepts. In this work, hidden Markov models (HMMs) are used to model four representative audio events, that is, gunshot, explosion, engine, and car braking, in action movies. At the semantic context level, generative (ergodic hidden Markov model) and discriminative (support vector machine (SVM)) approaches are investigated to fuse the characteristics and correlations among audio events, which provide cues for detecting gunplay and car-chasing scenes. The experimental results demonstrate the effectiveness of the proposed approaches and provide a preliminary framework for information mining by using audio characteristics.