Article

Effective image and video mining: an overview of model-based approaches

Authors:

Rokia Missaoui,

Roman M. PalenichkaAuthors Info & Claims

MDM '05: Proceedings of the 6th international workshop on Multimedia data mining: mining integrated media and complex data

Pages 43 - 52

https://doi.org/10.1145/1133890.1133895

Published: 21 August 2005 Publication History

Abstract

This paper is dedicated to revisiting image and video mining techniques from the viewpoint of image modeling approaches, which constitute the theoretical basis for these techniques. The most important areas belonging to image or video mining are: image knowledge extraction, content-based image retrieval, video retrieval, video sequence analysis, change detection, model learning, as well as object recognition. Traditionally, these areas have been developed independently, and hence have not benefited from some common sense approaches which provide potentially optimal and time-efficient solutions. Two different types of input data for knowledge extraction from an image collection or video sequences are considered: original image or symbolic (model) description of the image. Several basic models are described briefly and compared with each other in order to find effective solutions for the image and video mining problems. They include feature-based models and object-related structural models for the representation of spatial and temporal entities (objects, scenes or events).

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Effective image and video mining: an overview of model-based approaches
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Published In

cover image ACM Other conferences

MDM '05: Proceedings of the 6th international workshop on Multimedia data mining: mining integrated media and complex data

August 2005

107 pages

ISBN:159593216X

DOI:10.1145/1133890

Conference Chairs:
Fatma Bouali
University of Lille2, France
,
Latifur Khan
University of Texas at Dallas
,
Florent Masseglia
INRIA Sophia Antipolis, France

Copyright © 2005 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]

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Association for Computing Machinery

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Published: 21 August 2005

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Cited By

Ensafi MKeyvanpour MShojaedini S(2023)ABT: a comparative analytical survey on Analysis of Breast ThermogramsMultimedia Tools and Applications10.1007/s11042-023-17566-183:18(53293-53346)Online publication date: 17-Nov-2023
https://doi.org/10.1007/s11042-023-17566-1
Taşci T(2017)Image MiningBiometrics10.4018/978-1-5225-0983-7.ch008(157-185)Online publication date: 2017
https://doi.org/10.4018/978-1-5225-0983-7.ch008
Taşci T(2016)Image MiningIntelligent Techniques for Data Analysis in Diverse Settings10.4018/978-1-5225-0075-9.ch004(66-95)Online publication date: 2016
https://doi.org/10.4018/978-1-5225-0075-9.ch004
Vijayakumar VNedunchezhian R(2012)A study on video data miningInternational Journal of Multimedia Information Retrieval10.1007/s13735-012-0016-21:3(153-172)Online publication date: 25-Aug-2012
https://doi.org/10.1007/s13735-012-0016-2
Dao MBabaguchi NDoulamis Avan Gool LNixon MVarvarigou TDoulamis NSardis M(2008)Sports event detection using temporal patterns mining and web-casting textProceedings of the 1st ACM workshop on Analysis and retrieval of events/actions and workflows in video streams10.1145/1463542.1463549(33-40)Online publication date: 31-Oct-2008
https://dl.acm.org/doi/10.1145/1463542.1463549
Minh-Son Dao Noburu Babaguchi (2008)Mining temporal information and web-casting text for automatic sports event detection2008 IEEE 10th Workshop on Multimedia Signal Processing10.1109/MMSP.2008.4665150(616-621)Online publication date: Oct-2008
https://doi.org/10.1109/MMSP.2008.4665150

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