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| Content Provider | Springer Nature Link |
|---|---|
| Author | Elleuch, Nizar Ben Ammar, Anis Alimi, Adel M. |
| Copyright Year | 2014 |
| Abstract | Providing a semantic access to video data requires the development of concept detectors. However, semantic concepts detection is a hard task due to the large intra-class and the small inter-class variability of content. Moreover, semantic concepts co-occur together in various contexts and their occurrence may vary from one to another. Thus, it is interesting to exploit this knowledge in order to achieve satisfactory performances. In this paper we present a generic semantic video indexing scheme, called SVI_REGIMVid. It is based on three levels of analysis. The first level (level1) focuses on low-level processing such as video shot boundary/key-frame detection, annotation tools, key-points detection and visual features extraction tools. The second level (level2) aims to build the semantic models for supervised learning of concepts/contexts. The third level (level3) enriches the semantic interpretation of concepts/contexts by exploiting fuzzy knowledge. The obtained experimental results are promising for a semantic concept/context detection process. |
| Starting Page | 1397 |
| Ending Page | 1421 |
| Page Count | 25 |
| File Format | |
| ISSN | 13807501 |
| Journal | Multimedia Tools and Applications |
| Volume Number | 74 |
| Issue Number | 4 |
| e-ISSN | 15737721 |
| Language | English |
| Publisher | Springer US |
| Publisher Date | 2014-04-25 |
| Publisher Place | Boston |
| Access Restriction | One Nation One Subscription (ONOS) |
| Subject Keyword | Semantic indexing Concepts Contexts SVI_REGIMVid Multimedia Information Systems Computer Communication Networks Data Structures, Cryptology and Information Theory Special Purpose and Application-Based Systems |
| Content Type | Text |
| Resource Type | Article |
| Subject | Computer Networks and Communications Hardware and Architecture Software Media Technology |
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