A novel video mining system

A Anjulan; CN Canagarajah

doi:10.1109/ICIP.2007.4378922

A novel video mining system

A Anjulan, CN Canagarajah

Research output: Chapter in Book/Report/Conference proceeding › Conference Contribution (Conference Proceeding)

5 Citations (Scopus)

379 Downloads (Pure)

Abstract

This paper describes a novel object mining system for videos. An algorithm published in a previous paper by the authors is used to segment the video into shots and extract stable tracks from them. A grouping technique is introduced to combine these stable tracks into meaningful object clusters. These clusters are used in mining similar objects. Compared to other object mining systems, our approach mines more instances of similar objects in different shots. The proposed framework is applied to a full length feature film and improved results are shown.

Translated title of the contribution	A novel video mining system
Original language	English
Title of host publication	IEEE International Conference on Image Processing, 2007 (ICIP 2007), San Antonio
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
Pages	I-185 - I-188
Number of pages	4
Volume	I
ISBN (Print)	9781424414376
DOIs	https://doi.org/10.1109/ICIP.2007.4378922
Publication status	Published - Sept 2007
Event	International Conference on Image Processing - San Antonio, TX, United States Duration: 1 Sept 2007 → …

Conference

Conference	International Conference on Image Processing
Country/Territory	United States
City	San Antonio, TX
Period	1/09/07 → …

Bibliographical note

Rose publication type: Conference contribution

Terms of use: Copyright © 2007 IEEE. Reprinted from IEEE International Conference on Image Processing 2007 (ICIP 2007).

This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of the University of Bristol's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to [email protected].

By choosing to view this document, you agree to all provisions of the copyright laws protecting it.

Keywords

object mining
feature extraction
object clustering

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10.1109/ICIP.2007.4378922

Anjulan IEEE ICIP 2007Accepted author manuscript, 182 KB

http://hdl.handle.net/1983/1358

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title = "A novel video mining system",

abstract = "This paper describes a novel object mining system for videos. An algorithm published in a previous paper by the authors is used to segment the video into shots and extract stable tracks from them. A grouping technique is introduced to combine these stable tracks into meaningful object clusters. These clusters are used in mining similar objects. Compared to other object mining systems, our approach mines more instances of similar objects in different shots. The proposed framework is applied to a full length feature film and improved results are shown.",

keywords = "object mining, feature extraction, object clustering",

author = "A Anjulan and CN Canagarajah",

note = "Rose publication type: Conference contribution Terms of use: Copyright {\textcopyright} 2007 IEEE. Reprinted from IEEE International Conference on Image Processing 2007 (ICIP 2007). This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of the University of Bristol's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to [email protected]. By choosing to view this document, you agree to all provisions of the copyright laws protecting it. ; International Conference on Image Processing ; Conference date: 01-09-2007",

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AB - This paper describes a novel object mining system for videos. An algorithm published in a previous paper by the authors is used to segment the video into shots and extract stable tracks from them. A grouping technique is introduced to combine these stable tracks into meaningful object clusters. These clusters are used in mining similar objects. Compared to other object mining systems, our approach mines more instances of similar objects in different shots. The proposed framework is applied to a full length feature film and improved results are shown.

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KW - feature extraction

KW - object clustering

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DO - 10.1109/ICIP.2007.4378922

M3 - Conference Contribution (Conference Proceeding)

SN - 9781424414376

VL - I

SP - I-185 - I-188

BT - IEEE International Conference on Image Processing, 2007 (ICIP 2007), San Antonio

PB - Institute of Electrical and Electronics Engineers (IEEE)

T2 - International Conference on Image Processing

Y2 - 1 September 2007

ER -

A novel video mining system

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