skip to main content
10.1145/1862344.1862368acmotherconferencesArticle/Chapter ViewAbstractPublication PagessisapConference Proceedingsconference-collections
research-article

Sub-image searching through intersection of local descriptors

Published:18 September 2010Publication History

ABSTRACT

The complexity of search in current business intelligence systems, academic research, or even the home audiovisual databases grows up rapidly. Users require searching by the content of their data. For example, the user sees a cathedral while watching a movie and by taking a snapshot, his or her private collection of holiday photos can be searched for images containing that cathedral, as demonstrated in Figure 1. In practice, it is not sufficient to store data and search in it by exact match but rather by means of similarity, i.e. retrieving data items similar to a query item. Similarity searching is especially requested in multimedia databases, digital right management systems, computer aided diagnosis, but also in natural sciences and psychology. In these fields, theoretical primal background for querying by similarity is already defined.

References

  1. }}O. Chum, M. Perdoch, and J. Matas. Geometric min-hashing: Finding a (thick) needle in a haystack. CVPR, pages 17--24, 2009.Google ScholarGoogle ScholarCross RefCross Ref
  2. }}P. Ciaccia, M. Patella, and P. Zezula. M-tree: An efficient access method for similarity search in metric spaces. In VLDB, pages 426--435. Morgan Kaufmann, 1997. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. }}T. Homola, V. Dohnal, and P. Zezula. Proximity-based order-respecting intersection for searching in image databases. In Proceedings of the 8th International Workshop on Adaptive Multimedia Retrieval (AMR 2010), 2010. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. }}Y. Ke, R. Sukthankar, L. Huston, Y. Ke, and R. Sukthankar. Efficient near-duplicate detection and sub-image retrieval. In In ACM Multimedia, pages 869--876, 2004. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. }}D. G. Lowe. Distinctive image features from scale-invariant keypoints. Int. J. Comput. Vision, 60(2):91--110, 2004. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. }}M.-S. Ryu, S.-J. Park, and C. S. Won. Image retrieval using sub-image matching in photos using mpeg-7 descriptors. In AIRS, pages 366--373, 2005. Google ScholarGoogle ScholarDigital LibraryDigital Library

Index Terms

  1. Sub-image searching through intersection of local descriptors

                  Recommendations

                  Comments

                  Login options

                  Check if you have access through your login credentials or your institution to get full access on this article.

                  Sign in
                  • Published in

                    cover image ACM Other conferences
                    SISAP '10: Proceedings of the Third International Conference on SImilarity Search and APplications
                    September 2010
                    130 pages
                    ISBN:9781450304207
                    DOI:10.1145/1862344

                    Copyright © 2010 ACM

                    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]

                    Publisher

                    Association for Computing Machinery

                    New York, NY, United States

                    Publication History

                    • Published: 18 September 2010

                    Permissions

                    Request permissions about this article.

                    Request Permissions

                    Check for updates

                    Qualifiers

                    • research-article

                  PDF Format

                  View or Download as a PDF file.

                  PDF

                  eReader

                  View online with eReader.

                  eReader