From pixels to semantic spaces : advances in content-based image retrieval / | |
Autor: | Vasconcelos, Nuno. |
Tema(s): | |
Resumen: | The paradigm for image retrieval has evolved from low-level image representations to semantic concept models to higher-level semantic inferences. UCSD's Statistical Visual Computing Laboratory y has developed effective techniques for each paradigm that equate retrieval with classification and strive for minimum-probability-of-error optimality. In August 2006, Nielsen/NetRatings announced that five of the 10 fastest growing Web brands were user-generated content sites-platforms for photo or video sharing and blogs (www.nielsen-netratings.com/pr/PR_060810.PDF). Earlier statistics revealed that in April 2006 alone, the top five photo-sharing sites received close to 34 million unique US users (http://pic.photobucket.com/press/2006-06-PopPhoto.pdf) |
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The paradigm for image retrieval has evolved from low-level image representations to semantic concept models to higher-level semantic inferences. UCSD's Statistical Visual Computing Laboratory y has developed effective techniques for each paradigm that equate retrieval with classification and strive for minimum-probability-of-error optimality. In August 2006, Nielsen/NetRatings announced that five of the 10 fastest growing Web brands were user-generated content sites-platforms for photo or video sharing and blogs (www.nielsen-netratings.com/pr/PR_060810.PDF). Earlier statistics revealed that in April 2006 alone, the top five photo-sharing sites received close to 34 million unique US users (http://pic.photobucket.com/press/2006-06-PopPhoto.pdf)
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