Multimodal concept detection in broadcast media: KavTan

Date

2014-10-01

Author

SOYSAL, Medeni
Alatan, Abdullah Aydın
TEKİN, Mashar
ESEN, Ersin
SARACOĞLU, Ahmet
Acar, Banu Oskay
Ozan, Ezgi Can
Ates, Tugrul K.
SEVİMLİ, Hakan
SEVİNÇ, Muge
ATIL, Ilkay
Ozkan, Savas
Arabaci, Mehmet Ali
TANKIZ, Seda
KARADENİZ, Talha
ÖNÜR, Duygu
SELÇUK, Sezin
Alatan, A. Aydin
Çiloğlu, Tolga

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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Concept detection stands as an important problem for efficient indexing and retrieval in large video archives. In this work, the KavTan System, which performs high-level semantic classification in one of the largest TV archives of Turkey, is presented. In this system, concept detection is performed using generalized visual and audio concept detection modules that are supported by video text detection, audio keyword spotting and specialized audio-visual semantic detection components. The performance of the presented framework was assessed objectively over a wide range of semantic concepts (5 high-level, 14 visual, 9 audio, 2 supplementary) by using a significant amount of precisely labeled ground truth data. KavTan System achieves successful high-level concept detection performance in unconstrained TV broadcast by efficiently utilizing multimodal information that is systematically extracted from both spatial and temporal extent of multimedia data.

Subject Keywords

Media Technology, Computer Networks and Communications, Hardware and Architecture, Software

URI

https://hdl.handle.net/11511/42791

Journal

MULTIMEDIA TOOLS AND APPLICATIONS

DOI

https://doi.org/10.1007/s11042-013-1564-z

Collections

Department of Electrical and Electronics Engineering, Article

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Citation Formats

M. SOYSAL et al., “Multimodal concept detection in broadcast media: KavTan,” MULTIMEDIA TOOLS AND APPLICATIONS, pp. 2787–2832, 2014, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/42791.