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Vidico18 user page (under construction)

Imense

Imense Ltd is a UK based company that develops content based image retrieval and automatic image annotation technology. The founders of the company are Dr Christopher Town and Dr David Sinclair. In their academic lives they developed the first 'Ontological Query Evaluation Language' (OQUEL) for image retrieval. OQUEL mapped a plain text user query onto a query over automatically recognised visual content in a corpus of images.

Key papers describing the birth and evolution of ontological query languages include: [1] [2]

Technology derived in spirit from OQUEL is in routine use on the Imense PictureSearch portal. The user interface allows a user to type a plain text query that is probabilistically parsed to recognise visual aspects (like 'purple flowers in the center') and non visual aspects ('obscuring Tony Blaire's tie'). The issues associated with scaling up image search to cope with 10s of millions or more images were addressed with active support form the Science and Technology Facilities Council [3] and GridPP [4]. News articles about Imense search technology include [5] [6] [7].

Research

The research focus of Imense Ltd has moved towards semi automatic tagging of image through the use of statistical associative vocabularies, parametric face modeling [8] and visual similarity search as a means of re-ranking semantic queries.


References

[[Category:Internet search engines]] [[Category:Artificial intelligence applications]] [[Category:Applications of computer vision]]

From Wikipedia, the free encyclopedia

Vidico18 user page (under construction)

Imense

Imense Ltd is a UK based company that develops content based image retrieval and automatic image annotation technology. The founders of the company are Dr Christopher Town and Dr David Sinclair. In their academic lives they developed the first 'Ontological Query Evaluation Language' (OQUEL) for image retrieval. OQUEL mapped a plain text user query onto a query over automatically recognised visual content in a corpus of images.

Key papers describing the birth and evolution of ontological query languages include: [1] [2]

Technology derived in spirit from OQUEL is in routine use on the Imense PictureSearch portal. The user interface allows a user to type a plain text query that is probabilistically parsed to recognise visual aspects (like 'purple flowers in the center') and non visual aspects ('obscuring Tony Blaire's tie'). The issues associated with scaling up image search to cope with 10s of millions or more images were addressed with active support form the Science and Technology Facilities Council [3] and GridPP [4]. News articles about Imense search technology include [5] [6] [7].

Research

The research focus of Imense Ltd has moved towards semi automatic tagging of image through the use of statistical associative vocabularies, parametric face modeling [8] and visual similarity search as a means of re-ranking semantic queries.


References

[[Category:Internet search engines]] [[Category:Artificial intelligence applications]] [[Category:Applications of computer vision]]


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