Video Database Modeling and Temporal Pattern Retrieval using Hierarchical Markov Model Mediator

Na Zhao; Shu Ching Chen; Mei Ling Shyu

doi:10.1109/ICDEW.2006.162

Video Database Modeling and Temporal Pattern Retrieval using Hierarchical Markov Model Mediator

Na Zhao, Shu Ching Chen, Mei Ling Shyu

Electrical and Computer Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

7 Scopus citations

Abstract

The dream of pervasive multimedia retrieval and reuse will not be realized without incorporating semantics in the multimedia database. As video data is penetrating many information systems, the need for database support for video data evolves. Hence, we propose an innovative database modeling mechanism called Hierarchical Markov Model Mediator (HMMM) which integrates lowlevel features, semantic concepts, and high-level user perceptions for modeling and indexing multiple-level video objects to facilitate temporal pattern retrieval. Different from the existing database modeling methods, our approach carries a stochastic and dynamic process in both search and similarity calculation. In the retrieval of semantic event patterns, HMMM always tries to traverse the right path and therefore it can assist in retrieving more accurate patterns quickly with lower computational costs. Moreover, HMMM supports feedbacks and learning strategies, which can proficiently assure the continuous improvements of the overall performance.

Original language	English (US)
Title of host publication	ICDEW 2006 - Proceedings of the 22nd International Conference on Data Engineering Workshops
Editors	Xiaofang Zhou, Roger S. Barga
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	0769525717, 9780769525716
DOIs	https://doi.org/10.1109/ICDEW.2006.162
State	Published - 2006
Event	22nd International Conference on Data Engineering Workshops, ICDEW 2006 - Atlanta, United States Duration: Apr 3 2006 → Apr 7 2006

Publication series

Name	ICDEW 2006 - Proceedings of the 22nd International Conference on Data Engineering Workshops

Other

Other	22nd International Conference on Data Engineering Workshops, ICDEW 2006
Country	United States
City	Atlanta
Period	4/3/06 → 4/7/06

ASJC Scopus subject areas

Information Systems
Computer Networks and Communications
Information Systems and Management

Access to Document

10.1109/ICDEW.2006.162

Fingerprint Dive into the research topics of 'Video Database Modeling and Temporal Pattern Retrieval using Hierarchical Markov Model Mediator'. Together they form a unique fingerprint.

Cite this

Zhao, N., Chen, S. C., & Shyu, M. L. (2006). Video Database Modeling and Temporal Pattern Retrieval using Hierarchical Markov Model Mediator. In X. Zhou, & R. S. Barga (Eds.), ICDEW 2006 - Proceedings of the 22nd International Conference on Data Engineering Workshops [1623805] (ICDEW 2006 - Proceedings of the 22nd International Conference on Data Engineering Workshops). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICDEW.2006.162

Video Database Modeling and Temporal Pattern Retrieval using Hierarchical Markov Model Mediator. / Zhao, Na; Chen, Shu Ching; Shyu, Mei Ling.

ICDEW 2006 - Proceedings of the 22nd International Conference on Data Engineering Workshops. ed. / Xiaofang Zhou; Roger S. Barga. Institute of Electrical and Electronics Engineers Inc., 2006. 1623805 (ICDEW 2006 - Proceedings of the 22nd International Conference on Data Engineering Workshops).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Zhao, N, Chen, SC & Shyu, ML 2006, Video Database Modeling and Temporal Pattern Retrieval using Hierarchical Markov Model Mediator. in X Zhou & RS Barga (eds), ICDEW 2006 - Proceedings of the 22nd International Conference on Data Engineering Workshops., 1623805, ICDEW 2006 - Proceedings of the 22nd International Conference on Data Engineering Workshops, Institute of Electrical and Electronics Engineers Inc., 22nd International Conference on Data Engineering Workshops, ICDEW 2006, Atlanta, United States, 4/3/06. https://doi.org/10.1109/ICDEW.2006.162

Zhao N, Chen SC, Shyu ML. Video Database Modeling and Temporal Pattern Retrieval using Hierarchical Markov Model Mediator. In Zhou X, Barga RS, editors, ICDEW 2006 - Proceedings of the 22nd International Conference on Data Engineering Workshops. Institute of Electrical and Electronics Engineers Inc. 2006. 1623805. (ICDEW 2006 - Proceedings of the 22nd International Conference on Data Engineering Workshops). https://doi.org/10.1109/ICDEW.2006.162

Zhao, Na ; Chen, Shu Ching ; Shyu, Mei Ling. / Video Database Modeling and Temporal Pattern Retrieval using Hierarchical Markov Model Mediator. ICDEW 2006 - Proceedings of the 22nd International Conference on Data Engineering Workshops. editor / Xiaofang Zhou ; Roger S. Barga. Institute of Electrical and Electronics Engineers Inc., 2006. (ICDEW 2006 - Proceedings of the 22nd International Conference on Data Engineering Workshops).

@inproceedings{b8cc5a32806b47f5bc7c856a126b8a8b,

title = "Video Database Modeling and Temporal Pattern Retrieval using Hierarchical Markov Model Mediator",

abstract = "The dream of pervasive multimedia retrieval and reuse will not be realized without incorporating semantics in the multimedia database. As video data is penetrating many information systems, the need for database support for video data evolves. Hence, we propose an innovative database modeling mechanism called Hierarchical Markov Model Mediator (HMMM) which integrates lowlevel features, semantic concepts, and high-level user perceptions for modeling and indexing multiple-level video objects to facilitate temporal pattern retrieval. Different from the existing database modeling methods, our approach carries a stochastic and dynamic process in both search and similarity calculation. In the retrieval of semantic event patterns, HMMM always tries to traverse the right path and therefore it can assist in retrieving more accurate patterns quickly with lower computational costs. Moreover, HMMM supports feedbacks and learning strategies, which can proficiently assure the continuous improvements of the overall performance.",

author = "Na Zhao and Chen, {Shu Ching} and Shyu, {Mei Ling}",

note = "Funding Information: For Shu-Ching Chen, this research was supported in part by NSF EIA-0220562 and HRD-0317692. For Mei- Ling Shyu, this research was supported in part by NSF ITR (Medium) IIS-0325260; 22nd International Conference on Data Engineering Workshops, ICDEW 2006 ; Conference date: 03-04-2006 Through 07-04-2006",

year = "2006",

doi = "10.1109/ICDEW.2006.162",

language = "English (US)",

series = "ICDEW 2006 - Proceedings of the 22nd International Conference on Data Engineering Workshops",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

editor = "Xiaofang Zhou and Barga, {Roger S.}",

booktitle = "ICDEW 2006 - Proceedings of the 22nd International Conference on Data Engineering Workshops",

}

TY - GEN

T1 - Video Database Modeling and Temporal Pattern Retrieval using Hierarchical Markov Model Mediator

AU - Zhao, Na

AU - Chen, Shu Ching

AU - Shyu, Mei Ling

N1 - Funding Information: For Shu-Ching Chen, this research was supported in part by NSF EIA-0220562 and HRD-0317692. For Mei- Ling Shyu, this research was supported in part by NSF ITR (Medium) IIS-0325260

PY - 2006

Y1 - 2006

N2 - The dream of pervasive multimedia retrieval and reuse will not be realized without incorporating semantics in the multimedia database. As video data is penetrating many information systems, the need for database support for video data evolves. Hence, we propose an innovative database modeling mechanism called Hierarchical Markov Model Mediator (HMMM) which integrates lowlevel features, semantic concepts, and high-level user perceptions for modeling and indexing multiple-level video objects to facilitate temporal pattern retrieval. Different from the existing database modeling methods, our approach carries a stochastic and dynamic process in both search and similarity calculation. In the retrieval of semantic event patterns, HMMM always tries to traverse the right path and therefore it can assist in retrieving more accurate patterns quickly with lower computational costs. Moreover, HMMM supports feedbacks and learning strategies, which can proficiently assure the continuous improvements of the overall performance.

AB - The dream of pervasive multimedia retrieval and reuse will not be realized without incorporating semantics in the multimedia database. As video data is penetrating many information systems, the need for database support for video data evolves. Hence, we propose an innovative database modeling mechanism called Hierarchical Markov Model Mediator (HMMM) which integrates lowlevel features, semantic concepts, and high-level user perceptions for modeling and indexing multiple-level video objects to facilitate temporal pattern retrieval. Different from the existing database modeling methods, our approach carries a stochastic and dynamic process in both search and similarity calculation. In the retrieval of semantic event patterns, HMMM always tries to traverse the right path and therefore it can assist in retrieving more accurate patterns quickly with lower computational costs. Moreover, HMMM supports feedbacks and learning strategies, which can proficiently assure the continuous improvements of the overall performance.

UR - http://www.scopus.com/inward/record.url?scp=84879669557&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84879669557&partnerID=8YFLogxK

U2 - 10.1109/ICDEW.2006.162

DO - 10.1109/ICDEW.2006.162

M3 - Conference contribution

AN - SCOPUS:84879669557

T3 - ICDEW 2006 - Proceedings of the 22nd International Conference on Data Engineering Workshops

BT - ICDEW 2006 - Proceedings of the 22nd International Conference on Data Engineering Workshops

A2 - Zhou, Xiaofang

A2 - Barga, Roger S.

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 22nd International Conference on Data Engineering Workshops, ICDEW 2006

Y2 - 3 April 2006 through 7 April 2006

ER -