PUMA
Istituto di Scienza e Tecnologie dell'Informazione     
Rabitti F., Perego R., Falchi F., Lucchese C., Bolettieri P., Silvestri F., Piccioli T. CoPhIR (Content-based Photo Image Retrieval) Test-Collection.
 
 
Abstract
(English)
The CoPhIR (Content-based Photo Image Retrieval) Test-Collection has been developed to make significant tests on the scalability of the SAPIR project infrastructure (SAPIR: Search In Audio Visual Content Using Peer-to-peer IR) for similarity search. CoPhIR is now available to the research community to try and compare different indexing technologies for similarity search, with scalability being the key issue. We have extracted metadata from the Flickr archive, using the EGEE European GRID, through the DILIGENT project. For each image, the standard MPEG7 image feature have been extracted. Each entry of the test-bed contains: * The link to the corresponding entry into Flickr Web site * The photo image thumbnail * An XML structure with the Flickr user information in the corresponding Flickr entry: title, location, GPS, tags, comments, etc. * An XML structure with 5 extracted standard MPEG7 image features: o Scalable Colour o Colour Structure o Colour Layout o Edge Histogram o Homogeneous Texture The data collected so far represents the world largest multimedia metadata collection that is available for research on scalable similarity search techniques. It contains 106 million images.
URL: http://cophir.isti.cnr.it/
Subject Content Based Image Retrieval
Image Dayabase
Image Indexing
Similarity Search
Multimedia Big Data
I.4 IMAGE PROCESSING AND COMPUTER VISION



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