Paper
18 December 2003 Automatic textual annotation of video news based on semantic visual object extraction
Author Affiliations +
Abstract
In this paper, we present our work for automatic generation of textual metadata based on visual content analysis of video news. We present two methods for semantic object detection and recognition from a cross modal image-text thesaurus. These thesaurus represent a supervised association between models and semantic labels. This paper is concerned with two semantic objects: faces and Tv logos. In the first part, we present our work for efficient face detection and recogniton with automatic name generation. This method allows us also to suggest the textual annotation of shots close-up estimation. On the other hand, we were interested to automatically detect and recognize different Tv logos present on incoming different news from different Tv Channels. This work was done jointly with the French Tv Channel TF1 within the "MediaWorks" project that consists on an hybrid text-image indexing and retrieval plateform for video news.
© (2003) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Nozha Boujemaa, Francois Fleuret, Valerie Gouet, and Hichem Sahbi "Automatic textual annotation of video news based on semantic visual object extraction", Proc. SPIE 5307, Storage and Retrieval Methods and Applications for Multimedia 2004, (18 December 2003); https://doi.org/10.1117/12.529148
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CITATIONS
Cited by 3 scholarly publications.
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KEYWORDS
Video

Image processing

Facial recognition systems

Visualization

Semantic video

Lithium

Computer programming

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