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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Charara, N. Sokhn, M. Jarkass, I. Abou Khaled, O. Mugellini, E. |
| Copyright Year | 2014 |
| Description | Author affiliation: JUT, Lebanese Univ., Saida, Lebanon (Jarkass, I.) || HES-SO/FR, Fribourg, Switzerland (Abou Khaled, O.; Mugellini, E.) || Inst. of Inf. Syst., HES-SO/ Wallis, Sierre, Switzerland (Sokhn, M.) || EDST Lebanese Univ., Beirut, Lebanon (Charara, N.) |
| Abstract | This paper presents a novel supervised method for context modeling and classification based on Transferable Belief Model (TBM). The task of context classification is to identify, among predefined context types, the one that is currently active in the video-surveillance footage of multipurpose halls. Context is spatially modeled by extracting five discriminative semantic features according to depth zones. These zones are provided by depth-based scene segmentation method. Using mathematical TBM tools, the structured semantic features are processed and the mass functions are modeled on three levels in order to propose classification. In addition to video document indexing and retrieval, this work can improve the machine vision capability in behavior analysis. |
| Starting Page | 341 |
| Ending Page | 346 |
| File Size | 1192639 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781479947744 |
| ISSN | 21540373 |
| DOI | 10.1109/EIT.2014.6871788 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2014-06-05 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Context Context modeling Feature extraction Hidden Markov models Motion pictures Mathematical model Semantics video-surveillance context modeling pattern recognition transferable belief model |
| Content Type | Text |
| Resource Type | Article |
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