Motion-based video object tracking in the compressed domain

M Ritch; CN Canagarajah

doi:10.1109/ICIP.2007.4379581

Motion-based video object tracking in the compressed domain

M Ritch
, CN Canagarajah

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

14 Citations (Scopus)

449 Downloads (Pure)

Abstract

In this paper an algorithm for real-time unsupervised segmentation and tracking of a moving object is proposed. This is performed within the compressed domain using motion information only. Initial object segmentation is done using iterative rejection, taking advantage of its computational efficiency. The system seeks to overcome its disadvantages, namely a delay in object macroblocks appearing after consistency checking and non-identification of macroblocks containing object boundaries, by taking a model based approach to object tracking. The output of iterative rejection is used to update the model after tracking has taken place in each frame. Experimental results on a number of MPEG-2 encoded sequences demonstrate its effectiveness in identifying and tracking an object of interest from a compressed video stream and that the system is better than purely using iterative rejection as a segmentation method

Translated title of the contribution	Motion-based video object tracking in the compressed domain
Original language	English
Title of host publication	International Conference on Image Processing, San Antonio, TX
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
Pages	301 - 304
Volume	6
ISBN (Print)	9781424414376
DOIs	https://doi.org/10.1109/ICIP.2007.4379581
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

Conference Proceedings/Title of Journal: IEEE International Conference on Image Processing, 2007 (ICIP 2007)
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 i

Keywords

compressed domain
object tracking

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10.1109/ICIP.2007.4379581

Ritch IEEE ICIP 2007Accepted author manuscript, 446 KB

http://hdl.handle.net/1983/1531

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Cite this

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title = "Motion-based video object tracking in the compressed domain",

abstract = "In this paper an algorithm for real-time unsupervised segmentation and tracking of a moving object is proposed. This is performed within the compressed domain using motion information only. Initial object segmentation is done using iterative rejection, taking advantage of its computational efficiency. The system seeks to overcome its disadvantages, namely a delay in object macroblocks appearing after consistency checking and non-identification of macroblocks containing object boundaries, by taking a model based approach to object tracking. The output of iterative rejection is used to update the model after tracking has taken place in each frame. Experimental results on a number of MPEG-2 encoded sequences demonstrate its effectiveness in identifying and tracking an object of interest from a compressed video stream and that the system is better than purely using iterative rejection as a segmentation method",

keywords = "compressed domain, object tracking",

author = "M Ritch and CN Canagarajah",

note = "Conference Proceedings/Title of Journal: IEEE International Conference on Image Processing, 2007 (ICIP 2007) 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 i ; International Conference on Image Processing ; Conference date: 01-09-2007",

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AU - Canagarajah, CN

N1 - Conference Proceedings/Title of Journal: IEEE International Conference on Image Processing, 2007 (ICIP 2007) 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 i

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N2 - In this paper an algorithm for real-time unsupervised segmentation and tracking of a moving object is proposed. This is performed within the compressed domain using motion information only. Initial object segmentation is done using iterative rejection, taking advantage of its computational efficiency. The system seeks to overcome its disadvantages, namely a delay in object macroblocks appearing after consistency checking and non-identification of macroblocks containing object boundaries, by taking a model based approach to object tracking. The output of iterative rejection is used to update the model after tracking has taken place in each frame. Experimental results on a number of MPEG-2 encoded sequences demonstrate its effectiveness in identifying and tracking an object of interest from a compressed video stream and that the system is better than purely using iterative rejection as a segmentation method

AB - In this paper an algorithm for real-time unsupervised segmentation and tracking of a moving object is proposed. This is performed within the compressed domain using motion information only. Initial object segmentation is done using iterative rejection, taking advantage of its computational efficiency. The system seeks to overcome its disadvantages, namely a delay in object macroblocks appearing after consistency checking and non-identification of macroblocks containing object boundaries, by taking a model based approach to object tracking. The output of iterative rejection is used to update the model after tracking has taken place in each frame. Experimental results on a number of MPEG-2 encoded sequences demonstrate its effectiveness in identifying and tracking an object of interest from a compressed video stream and that the system is better than purely using iterative rejection as a segmentation method

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KW - object tracking

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DO - 10.1109/ICIP.2007.4379581

M3 - Conference Contribution (Conference Proceeding)

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EP - 304

BT - International Conference on Image Processing, San Antonio, TX

PB - Institute of Electrical and Electronics Engineers (IEEE)

T2 - International Conference on Image Processing

Y2 - 1 September 2007

ER -

Motion-based video object tracking in the compressed domain

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