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.
Author: | Prof. Dr. Ronald Glasberg, Sebastian Schmiedeke, Pascal Kelm, Thomas Sikora |
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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): | Creative Commons - Namensnennung-Nicht kommerziell-Keine Bearbeitung |