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Image retrieval at memory's edge: known image search based on user-drawn sketches

Authors:

Michael Springmann,

Ihab Al Kabary,

Heiko SchuldtAuthors Info & Claims

CIKM '10: Proceedings of the 19th ACM international conference on Information and knowledge management

Pages 1465 - 1468

https://doi.org/10.1145/1871437.1871648

Published: 26 October 2010 Publication History

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Abstract

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 the QbS system that provides CBIR based on user-drawn sketches. The QbS 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 the QbS 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.

References

[1]

A. Chalechale, A. Mertins, and G. Naghdy. Edge Image Description using Angular Radial Partitioning. IEE Proc. on Vision, Image & Signal Processing, 151(2):93--101, 2004.

Crossref

Google Scholar

[2]

A. Chalechale, G. Naghdy, and A. Mertins. Sketch-based image matching using angular partitioning. IEEE Transactions on Systems, Man and Cybernetics, 35(1):28--41, 2005.

Digital Library

Google Scholar

[3]

M. J. Huiskes and M. S. Lew. The MIR Flickr Retrieval Evaluation. In Proc. MIR'08, 2008.

Digital Library

Google Scholar

[4]

D. Keysers, T. Deselaers, C. Gollan, and H. Ney. Deformation models for image recognition. IEEE Trans. on Pattern Analysis and Machine Intelligence, 29(8):1422--1435, 2007.

Digital Library

Google Scholar

[5]

M. Springmann, I. Al Kabary, and H. Schuldt. Experiences with QbS: Challenges and evaluation of known image search based on user-drawn sketches. Tech. Report CS-2010-001, University of Basel, 2010.

Google Scholar

[6]

M. Springmann, D. Kopp, and H. Schuldt. Qbs - searching for known images using user-drawn sketches. In Proc. MIR 2010, pages 417--420, March 2010.

Digital Library

Google Scholar

[7]

H. I. Xie. Planned and Situated Aspects in Interactive IR: Patterns of User Interactive Intentions and Information Seeking Strategies. In Proc. ASIS, pages 101--110, 1997.

Google Scholar

Cited By

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Jin CLi CWang ZZhang YZhang T(2016)Sketch-Based Image Retrieval with a Novel BoVW RepresentationProceedings, Part I, of the 22nd International Conference on MultiMedia Modeling - Volume 951610.1007/978-3-319-27671-7_52(621-631)Online publication date: 4-Jan-2016
https://dl.acm.org/doi/10.1007/978-3-319-27671-7_52
Jin CWang ZZhang TZhu QZhang YHauptmann ANgo CXue XJiang YSnoek CVasconcelos N(2015)A Novel Visual-Region-Descriptor-based Approach to Sketch-based Image RetrievalProceedings of the 5th ACM on International Conference on Multimedia Retrieval10.1145/2671188.2749302(267-274)Online publication date: 22-Jun-2015
https://dl.acm.org/doi/10.1145/2671188.2749302
Giangreco ISpringmann MKabary ISchuldt H(2012)A user interface for query-by-sketch based image retrieval with color sketchesProceedings of the 34th European conference on Advances in Information Retrieval10.1007/978-3-642-28997-2_67(571-572)Online publication date: 1-Apr-2012
https://dl.acm.org/doi/10.1007/978-3-642-28997-2_67
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Index Terms

Image retrieval at memory's edge: known image search based on user-drawn sketches
1. Human-centered computing
  1. Human computer interaction (HCI)
    1. Interaction devices
      1. Touch screens
2. Information systems
  1. Information retrieval
    1. Information retrieval query processing
    2. Retrieval models and ranking

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Published In

CIKM '10: Proceedings of the 19th ACM international conference on Information and knowledge management

October 2010

2036 pages

ISBN:9781450300995

DOI:10.1145/1871437

General Chair:
Jimmy Huang
York University, Canada
,
Program Chairs:
Nick Koudas
University of Toronto, Canada
,
Gareth Jones
Dublin City University, Ireland
,
Xindong Wu
University of Vermont, USA
,
Kevyn Collins-Thompson
Microsoft Research, USA
,
Aijun An
York University, Canada

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 26 October 2010

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CIKM '10: International Conference on Information and Knowledge Management

October 26 - 30, 2010

ON, Toronto, Canada

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Overall Acceptance Rate 1,861 of 8,427 submissions, 22%

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Cited By

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Jin CLi CWang ZZhang YZhang T(2016)Sketch-Based Image Retrieval with a Novel BoVW RepresentationProceedings, Part I, of the 22nd International Conference on MultiMedia Modeling - Volume 951610.1007/978-3-319-27671-7_52(621-631)Online publication date: 4-Jan-2016
https://dl.acm.org/doi/10.1007/978-3-319-27671-7_52
Jin CWang ZZhang TZhu QZhang YHauptmann ANgo CXue XJiang YSnoek CVasconcelos N(2015)A Novel Visual-Region-Descriptor-based Approach to Sketch-based Image RetrievalProceedings of the 5th ACM on International Conference on Multimedia Retrieval10.1145/2671188.2749302(267-274)Online publication date: 22-Jun-2015
https://dl.acm.org/doi/10.1145/2671188.2749302
Giangreco ISpringmann MKabary ISchuldt H(2012)A user interface for query-by-sketch based image retrieval with color sketchesProceedings of the 34th European conference on Advances in Information Retrieval10.1007/978-3-642-28997-2_67(571-572)Online publication date: 1-Apr-2012
https://dl.acm.org/doi/10.1007/978-3-642-28997-2_67
Kreuzer RSpringmann MKabary ISchuldt H(2012)An interactive paper and digital pen interface for query-by-sketch image retrievalProceedings of the 34th European conference on Advances in Information Retrieval10.1007/978-3-642-28997-2_27(317-328)Online publication date: 1-Apr-2012
https://dl.acm.org/doi/10.1007/978-3-642-28997-2_27

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QbS: searching for known images using user-drawn sketches

Content-Based Medical Image Retrieval for Medical Radiology Images

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