- Tag-based Video Retrieval by Embedding Semantic Content in a Continuous Word Space
- IEEE Winter Conference on Applications of Computer Vision
- Book/source title
- 2016 IEEE Winter Conference on Applications of Computer Vision: WACV 2016: Lake Placid, New York, USA, 7-10 March 2016
- Pages (from-to)
- Piscataway, NJ: Institute of Electrical and Electronic Engineers
- Document type
- Conference contribution
- Faculty of Science (FNWI)
- Informatics Institute (IVI)
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.
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