Audio-visual video classification system design: For Arabic News domain
| Author | Dandashi, Amal |
| Author | Aljaam, Jihad |
| Author | Foufou, Sebti |
| Available date | 2020-11-26T11:21:08Z |
| Publication Date | 2017 |
| Publication Name | Proceedings - 2016 International Conference on Computational Science and Computational Intelligence, CSCI 2016 |
| Resource | Scopus |
| Abstract | There are many research initiatives tackling automated multimodal video classification, however very few of them are targeted towards classifying Arabic news-related videos. In light of the vast proliferation of raw digital Arabic data, specifically videos, over the internet, uncategorized and unused, we propose a new system to tackle this problem. The proposed system design consists of visual features extraction and classification, combined with audio-based event classification, as well semantic-content processing. Results are to be combined and documented using multimedia classification fusion techniques. We also propose to develop a new Arabic dataset based on news channel videos as well as raw videos from various online sources for testing and evaluation. |
| Sponsor | This publication was made possible by GSRA grant # 1-1-1202-13026 from the Qatar National Research Fund (a member of Qatar Foundation). |
| Language | en |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Subject | audio feature extraction Multimodal video classification named entity recognition news videos visual features |
| Type | Conference |
| Pagination | 745-751 |
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