Graph grammar based object recognition for image retrieval

Klauck, Christoph

doi:10.1007/3-540-60793-5_109

Cited by 2 publications

(1 citation statement)

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“…The results build hypotheses related to the primitive objects. In a second step we combine the hypotheses about the primitive objects according to the compositional semantics of more complex objects by means of which the hypotheses becomes a thesis [15]. For both steps we use neighborhood-controlled node-labeled and node-attributed feature graph grammars (I-NRCFGG) as specified in [14].…”

Section: Seman Tical Description With Graph Grammarsmentioning

confidence: 99%

Syntactical and Semantical Description of Video Sequences

1999

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Archiving, processing, and intelligent retrieval of digital video sequences can be efficiently solved by a high-level representation of video sequences. We describe a complete system for encoding the contents of video sequences based on their syntactical and semantical description. Our techniques are built on two phases: analysis and synthesis. The analysis phase involves the automatic generation of a syntactical structure using image and imagesequence analysis, image understanding as well as text recognition. Moreover, the syntactical description of images will be completed by a semantical understanding of video sequences. The full representation of video sequences will be generated during the synthesis phase by combining results from the analysis phase. Our developed prototype system is planned to be integrated into the cooperative work of a TV-team of the TV-station "Radio Bremen". Additionally, we describe some special functionality: scene analysis by clustering of video sequences with the aim of identifying a typical video genre. The latter is an useful approach for automatic trailer generation and for intelligent video editing as add-on for a video-cut-system.

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Section: Seman Tical Description With Graph Grammarsmentioning

confidence: 99%