Semantic Class Detectors in Video Genre Recognition

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F12%3APU98155" target="_blank" >RIV/00216305:26230/12:PU98155 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Result language
angličtina
Original language name
Semantic Class Detectors in Video Genre Recognition
Original language description
This paper presents our approach to video genre recognition which we developed for MediaEval 2011 evaluation. We treat the genre recognition task as a classification problem. We encode visual information in standard way using local features and Bag of Word representation. Audio channel is parameterized in similar way starting from its spectrogram. Further, we exploit available automatic speech transcripts and user generated meta-data for which we compute BOW representations as well. It is reasonable toexpect that semantic content of a video is strongly related to its genre, and if this semantic information was available it would make genre recognition simpler and more reliable. To this end, we used annotations for 345 semantic classes from TRECVID 2011 semantic indexing task to train semantic class detectors. Responses of these detectors were then used as features for genre recognition. The paper explains the approach in detail, it shows relative performance of the individual feature
Czech name
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Czech description
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Project
<a href="/en/project/7E11024" target="_blank" >7E11024: Together Anywhere, Together Anytime - Enlarged European Union</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>Z - Vyzkumny zamer (s odkazem do CEZ)<br>S - Specificky vyzkum na vysokych skolach

Publication year
2012
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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