Article

Semantic image retrieval based on probabilistic latent semantic analysis

Authors:

Amin Shah-hosseini,

Gerald M. KnappAuthors Info & Claims

MM '06: Proceedings of the 14th ACM international conference on Multimedia

Pages 703 - 706

https://doi.org/10.1145/1180639.1180788

Published: 23 October 2006 Publication History

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Abstract

Content-based image retrieval (CBIR) systems combine computer vision techniques and learning methodologies to find images in the database similar to the query images. Relevance feedback methods are introduced to the CBIR area as a tool to help the user to guide the retrieval system during the search process. Search history of the retrieval system, which is the accumulated feedbacks from past retrievals, has been recently used as a prior knowledge to improve the image retrieval performance. In this paper, we introduce an image retrieval model based on probabilistic latent semantic analysis (PLSA) that utilizes the system's search history to find hidden image semantics of the database. Image features are integrated to the model as well. The model is capable of detecting images and image features that efficiently represent semantic classes in the database. We demonstrate the effectiveness of our approach by comparing to previous work in this area.

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He, X., King O., Ma, W., Li, M., Zhang, H. Learning a semantic space from user's relevance feedback for image retrieval. IEEE Transactions on Circuits and Systems for Video Technology, 13(1), 2003, 39--48

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Cited By

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Figuera PGarcía Bringas P(2024)Revisiting Probabilistic Latent Semantic Analysis: Extensions, Challenges and InsightsTechnologies10.3390/technologies1201000512:1(5)Online publication date: 3-Jan-2024
https://doi.org/10.3390/technologies12010005
Han KChien WChiu CCheng Y(2020)Application of Support Vector Machine (SVM) in the Sentiment Analysis of Twitter DataSetApplied Sciences10.3390/app1003112510:3(1125)Online publication date: 7-Feb-2020
https://doi.org/10.3390/app10031125
Thomee BLew M(2012)Interactive search in image retrieval: a surveyInternational Journal of Multimedia Information Retrieval10.1007/s13735-012-0014-41:2(71-86)Online publication date: 8-Jun-2012
https://doi.org/10.1007/s13735-012-0014-4
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Index Terms

Semantic image retrieval based on probabilistic latent semantic analysis
1. Information systems
  1. Information retrieval

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Information & Contributors

Information

Published In

MM '06: Proceedings of the 14th ACM international conference on Multimedia

October 2006

1072 pages

ISBN:1595934472

DOI:10.1145/1180639

General Chairs:
Klara Nahrstedt
UIUC
,
Matthew Turk
UCSB
,
Program Chairs:
Yong Rui
Microsoft Research
,
Wolfgang Klas
Universität Wien
,
Ketan Mayer-Patel
UNC

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 23 October 2006

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MM06

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MM06: The 14th ACM International Conference on Multimedia 2006

October 23 - 27, 2006

CA, Santa Barbara, USA

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Overall Acceptance Rate 2,145 of 8,556 submissions, 25%

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Cited By

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Figuera PGarcía Bringas P(2024)Revisiting Probabilistic Latent Semantic Analysis: Extensions, Challenges and InsightsTechnologies10.3390/technologies1201000512:1(5)Online publication date: 3-Jan-2024
https://doi.org/10.3390/technologies12010005
Han KChien WChiu CCheng Y(2020)Application of Support Vector Machine (SVM) in the Sentiment Analysis of Twitter DataSetApplied Sciences10.3390/app1003112510:3(1125)Online publication date: 7-Feb-2020
https://doi.org/10.3390/app10031125
Thomee BLew M(2012)Interactive search in image retrieval: a surveyInternational Journal of Multimedia Information Retrieval10.1007/s13735-012-0014-41:2(71-86)Online publication date: 8-Jun-2012
https://doi.org/10.1007/s13735-012-0014-4
Lu ZIp H(2010)Combining Context, Consistency, and Diversity Cues for Interactive Image CategorizationIEEE Transactions on Multimedia10.1109/TMM.2010.204110012:3(194-203)Online publication date: 1-Apr-2010
https://dl.acm.org/doi/10.1109/TMM.2010.2041100
Oussalah M(2008)Content Based Image Retrieval: Review of State of Art and Future Directions2008 First Workshops on Image Processing Theory, Tools and Applications10.1109/IPTA.2008.4743799(1-10)Online publication date: Nov-2008
https://doi.org/10.1109/IPTA.2008.4743799

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Image retrieval based on indexing and relevance feedback

On-line content-based image retrieval system using joint querying and relevance feedback scheme

Prior-based probabilistic latent semantic analysis for multimedia retrieval