Depth Based Context Modeling and Classification in Video-surveillance
| Publicatietype: | In proceedings |
| Citatie: | |
| Boektitel: | Proceedings of the International Conference on Machine Vision and Machine Learning |
| Jaar: | 2014 |
| Maand: | Augustus |
| Locatie: | Prague, Czech Republic |
| Organisatie: | International Conference on Machine Vision and Machine Learning, 14-15.08.2014 |
| Samenvatting: | With a dedicated definition of ‘Context’ in image understanding systems, we present in this paper a novel context modelling and classification system. The main goal behind multimodal context modelling is to identify the context type from video-surveillance footage of multipurpose halls. First, the distribution of the different zones in a multipurpose hall is automatically captured using a dedicated depth based segmentation method. The discriminative description is illustrated by extracting five semantic features according to depth zones. These features are processed with the Transferable Belief Model to propose a classification. Results show the validity of the method for context recognition. |
| Trefwoorden: | Context modelling, Pattern Recognition, Scene segmentation, Video-surveillance |
| Auteurs | |
| Toegevoegd door: | [] |
| Totaalscore: | 0 |
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