research-article

Robust GME in encoded MPEG video

Authors:

Hamid Reza PourrezaAuthors Info & Claims

MoMM '11: Proceedings of the 9th International Conference on Advances in Mobile Computing and Multimedia

Pages 147 - 154

https://doi.org/10.1145/2095697.2095724

Published: 05 December 2011 Publication History

Abstract

In this paper, we propose a novel block-based approach for global motion estimation (GME) and panorama image construction in encoded MPEG-1 video streams. Direct extraction of motion vectors (MV) from MPEG stream greatly improves efficiency of our method against pixel-based methods. However, some MVs in MPEG stream do not indicate real object or camera motion in the scene. Therefore, we introduce a reliability measure to discriminate real MVs from noisy or outlier MVs. In addition, an iterative reweighting process is applied to increase accuracy of GME. Finally, panorama image of several sequences is constructed by using estimated camera motion. Experiments show that the proposed method has high accuracy and can produce high quality panorama images for compressed videos faster than realtime.

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Cited By

Meng ZSánchez JMorel JBertozzi ABrantingham P(2018)Ego-Motion Classification for Body-Worn VideosImaging, Vision and Learning Based on Optimization and PDEs10.1007/978-3-319-91274-5_10(221-239)Online publication date: 20-Nov-2018
https://doi.org/10.1007/978-3-319-91274-5_10
Kiani VPourreza H(2013)Flexible soccer video summarization in compressed domainICCKE 201310.1109/ICCKE.2013.6682798(213-218)Online publication date: Oct-2013
https://doi.org/10.1109/ICCKE.2013.6682798

Index Terms

Robust GME in encoded MPEG video
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
  2. Computer graphics
    1. Animation
      1. Motion capture
      2. Motion processing

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Published In

cover image ACM Other conferences

MoMM '11: Proceedings of the 9th International Conference on Advances in Mobile Computing and Multimedia

December 2011

318 pages

ISBN:9781450307857

DOI:10.1145/2095697

Conference Chair:
Wenny Rahayu
La Trobe University, Australia
,
General Chairs:
Eric Pardede
La Trobe University, Australia
,
Nguyen Duc Cuong
International University (VNU-HCMC), Vietnam
,
Program Chair:
David Taniar
Monash University, Australia

Copyright © 2011 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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Publication History

Published: 05 December 2011

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MoMM '11

MoMM '11: The 9th International Conference on Advances in Mobile Computing & Multimedia

December 5 - 7, 2011

Ho Chi Minh City, Vietnam

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Cited By

Meng ZSánchez JMorel JBertozzi ABrantingham P(2018)Ego-Motion Classification for Body-Worn VideosImaging, Vision and Learning Based on Optimization and PDEs10.1007/978-3-319-91274-5_10(221-239)Online publication date: 20-Nov-2018
https://doi.org/10.1007/978-3-319-91274-5_10
Kiani VPourreza H(2013)Flexible soccer video summarization in compressed domainICCKE 201310.1109/ICCKE.2013.6682798(213-218)Online publication date: Oct-2013
https://doi.org/10.1109/ICCKE.2013.6682798

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