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An Automatic System for Real-Time Video-Genres Detection Using High-Level Descriptors and a Set of Classifiers

  • We present a new approach for classifying MPEG-2 video sequences as dasiacartoonpsila, dasiacommercialpsila, dasiamusicpsila, dasianewspsila or dasiasportpsila by analyzing specific, high-level audio-visual features of consecutive frames in real-time. This is part of the well-known video-genre-classification problem, where popular TV-broadcast genres are studied. Such applications have also been discussed in the context of MPEG-7 [1]. In our method the extracted features are logically combined using a set of classifiers to produce a reliable recognition. The results demonstrate a high identification rate based on a large representative collection of 100 video sequences (20 sequences per genre) gathered from free digital TV-broadcasting in Europe.
Metadaten
Author:Prof. Dr. Ronald Glasberg, Sebastian Schmiedeke, Pascal Kelm, Thomas Sikora
Document Type:Conference Proceeding/Conference Report
Language:English
Date of Publication (online):2016/07/19
Year of first Publication:2008
Publishing Institution:SRH Berlin University of Applied Sciences
Release Date:2016/07/19
Tag:Consumer Electronics; Video Gaming
Note:
Volltext aus urheberrechtlichen Gründen nicht verfügbar.
Fulltext due to copyright not available.
Link author profile:https://www.srh-berlin.de/hochschule/hochschulteam/glasberg-ronald/
Date:04/2008
Convention/Event:IEEE 12th International Symposium on Consumer Electronics
Location:Algarve, Portugal
JEL-Classification:Y Miscellaneous Categories
Licence (German):License LogoCreative Commons - Namensnennung-Nicht kommerziell-Keine Bearbeitung
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