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EXTENT: fusing context, content, and semantic ontology for photo annotation
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Source ACM International Conference Proceeding Series; Vol. 160 archive
Proceedings of the 2nd international workshop on Computer vision meets databases table of contents
Baltimore, MD
SESSION: Multimedia modeling and querying table of contents
Pages: 5 - 11  
Year of Publication: 2005
ISBN:1-59593-151-1
Author
Edward Y. Chang  VIMA Technologies, Santa Barbara, California
Publisher
ACM  New York, NY, USA
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ABSTRACT

This architecture paper presents EXTENT, a probabilistic framework that uses influence diagrams to fuse metadata of multiple modalities for photo annotation. EXTENT fuses contextual information (location, time, and camera parameters), photo content (perceptual features), and semantic ontology in a synergistic way. It uses causal strengths to encode causalities between variables, and between variables and semantic labels. Through a landmark-recognition case study, we show that EXTENT can provide high-quality annotation, substantially better than any traditional unimodal methods.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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