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UvA-DARE ( Digital Academic Repository ) Tag-based Video Retrieval by Embedding Semantic Content in a Continuous Word
| Content Provider | Semantic Scholar |
|---|---|
| Author | Agharwal Snoek |
| Copyright Year | 2016 |
| Abstract | Content-based event retrieval in unconstrained web videos, based on query tags, is a hard problem due to large intra-class variances, and limited vocabulary and accuracy of the video concept detectors, creating a “semantic query gap”. We present a technique to overcome this gap by using continuous word space representations to explicitly compute query and detector concept similarity. This not only allows for fast query-video similarity computation with implicit query expansion, but leads to a compact video representation, which allows implementation of a real-time retrieval system that can fit several thousand videos in a few hundred megabytes of memory. We evaluate the effectiveness of our representation on the challenging NIST MEDTest 2014 dataset. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | https://pure.uva.nl/ws/files/2779402/175913_AgharwalWCACV2016.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
