Image Retrieval at Memory’s Edge: Known Image Search based on User-Drawn Sketches

Springmann, Michael and Al Kabary, Ihab and Schuldt, Heiko. (2010) Image Retrieval at Memory’s Edge: Known Image Search based on User-Drawn Sketches. In: Proceedings of the 19th ACM International Conference on Information and Knowledge Management (CIKM 2010). New York, pp. 1465-1468.

Full text not available from this repository.

Official URL: http://edoc.unibas.ch/dok/A5839815

Downloads: Statistics Overview


With the increasingly growing size of digital image collections, known image search is gaining more and more importance. Especially in collections where individual objects are not tagged with metadata describing their content, content-based image retrieval (CBIR) is a promising approach, but usually suffers from the unavailability of query images that are good enough to express the user's information need. In this paper, we present a system that provides CBIR based on user-drawn sketches. The system combines angular radial partitioning for the extraction of features in the user-provided sketch, taking into account the spatial distribution of edges, and the image distortion model. This combination offers several highly relevant invariances that allow the query sketch to slightly deviate from the searched image in terms of rotation, translation, relative size, and/or unknown objects in the background. To illustrate the benefits of the approach, we present search results from the evaluation of our system on the basis of the MIRFLICKR collection with 25,000 objects and compare the retrieval results of pure metadata-driven approaches, pure content-based retrieval using different sketches, and combinations thereof.
Faculties and Departments:05 Faculty of Science > Departement Mathematik und Informatik > Informatik > Datenbanken (Schuldt)
UniBasel Contributors:Schuldt, Heiko and Springmann, Michael and El-Kabary, Ihab
Item Type:Conference or Workshop Item, refereed
Conference or workshop item Subtype:Conference Paper
Note:Publication type according to Uni Basel Research Database: Conference paper
Identification Number:
Last Modified:08 Jun 2012 06:55
Deposited On:08 Jun 2012 06:45

Repository Staff Only: item control page