A descriptor for large scale image retrieval based on sketched feature lines

dc.contributor.authorEitz, Mathiasen_US
dc.contributor.authorHildebrand, Kristianen_US
dc.contributor.authorBoubekeur, Tamyen_US
dc.contributor.authorAlexa, Marcen_US
dc.contributor.editorCindy Grimm and Joseph J. LaViola, Jr.en_US
dc.date.accessioned2014-01-28T18:04:15Z
dc.date.available2014-01-28T18:04:15Z
dc.date.issued2009en_US
dc.description.abstractWe address the problem of large scale sketch based image retrieval, searching in a database of over a million images. The search is based on a descriptor that elegantly addresses the asymmetry between the binary user sketch on the one hand and the full color image on the other hand. The proposed descriptor is constructed such that both the full color image and the sketch undergo exactly the same preprocessing steps. We also design an adapted version of the descriptor proposed for MPEG-7 and compare their performance on a database of 1.5 million images. Best matching images are clustered based on color histograms, to offset the lacking color in the query. Overall, the query results demonstrate that the system allows users an intuitive access to large image databases.en_US
dc.description.seriesinformationEUROGRAPHICS Workshop on Sketch-Based Interfaces and Modelingen_US
dc.identifier.isbn978-3-905674-19-4en_US
dc.identifier.issn1812-3503en_US
dc.identifier.urihttps://doi.org/10.2312/SBM/SBM09/029-036en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectCategories and Subject Descriptors (according to ACM CCS): H.3.1 [Information Storage and Retrieval]: Content Analysis and Indexing-Indexing methodsen_US
dc.titleA descriptor for large scale image retrieval based on sketched feature linesen_US
Files
Original bundle
Now showing 1 - 2 of 2
Loading...
Thumbnail Image
Name:
029-036.pdf
Size:
16.13 MB
Format:
Adobe Portable Document Format
No Thumbnail Available
Name:
SBIR_final.mp4
Size:
58.44 MB
Format:
Unknown data format