Abstract
In E-learning, structure analysis of lecture video is the first step for effective and efficient indexing, browsing and retrieval. A hierarchical model of narrative structure for lecture video is introduced. The root is lecture video; the next is layer of narrative elements conveying meaningful information in semantics; then is narrative features layer closely to both visual and auditory physical features. A framework is proposed to analyze narrative structure. Extraction of narrative features is described as well. Hierarchical hidden Markov model is introduced to determine the parameters and detect narrative elements automatically.
Supported by the Natural Science Fund of China(No.60473117).
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Dorai, C., Oria, V., Neelavalli, V.: Structuralizing educational videos based on presentation content. In: ICME 2003 (2003)
Liu, Y.: Fast video segment retrieval by sort-merge feature selection, boundary refinement and lazy evaluation. Computer Vision and Image Understanding 92, 147–175 (2003)
Fine, S., Singer, Y., Tishby, N.: The hierarchical hidden markov model: Analysis and applications. Machine Learning 32, 41–62 (1998)
Murphy, K., Paskin, M.: Linear time inference in hierarchical hidden Markov models. In: Proceedings of Neural Information Processing Systems (2001)
Naphade, M., Huang, T.: Discovering recurrent events in video using unsupervised methods. In: Proc. Intl. Conf. Image Processing (2002)
Xie, L., Chang, S.-F., Divakaran, A., Sun, H.: Unsupervised discovery of multilevel statistical video structures using hierarchical hidden Markov models. In: Interational Conference on Multimedia and Expo. (2003)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2006 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Liu, YC., Luan, XD., Xie, YX., Dai, DH., Wu, LD. (2006). Narrative Structure Analysis of Lecture Video with Hierarchical Hidden Markov Model for E-Learning. In: Pan, Z., Aylett, R., Diener, H., Jin, X., Göbel, S., Li, L. (eds) Technologies for E-Learning and Digital Entertainment. Edutainment 2006. Lecture Notes in Computer Science, vol 3942. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11736639_54
Download citation
DOI: https://doi.org/10.1007/11736639_54
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-33423-1
Online ISBN: 978-3-540-33424-8
eBook Packages: Computer ScienceComputer Science (R0)