Article

Video parsing based on head tracking and face recognition

Authors:

Chang HuangAuthors Info & Claims

CIVR '07: Proceedings of the 6th ACM international conference on Image and video retrieval

Pages 57 - 64

https://doi.org/10.1145/1282280.1282288

Published: 09 July 2007 Publication History

Abstract

In this paper, we describe a fully automatic video retrieval prototype system that uses an image or a video sequence of an interested identity as probe. The system is based on face vision techniques including face detection and tracking, face alignment and recognition. Given a film or TV sitcom, first face trajectories are extracted in video by head tracking that decompose the video into segments corresponding to certain identity, then frames containing faces of higher quality are selected and normalized according to face alignment results, and finally different segments are associated by face recognition. Experiments are carried out on news video, feature length film video and TV sitcom to show its effectiveness. Potential usage of our system includes intelligent DVD/VCD browsing, video database retrieval, meeting record browsing, etc.

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Cited By

Chacon-Murguia MUrias-Zavala D(2014)A DTCNN Approach on Video Analysis: Dynamic and Static Object SegmentationRecent Advances on Hybrid Approaches for Designing Intelligent Systems10.1007/978-3-319-05170-3_22(315-336)Online publication date: 27-Mar-2014
https://doi.org/10.1007/978-3-319-05170-3_22
Jammalamadaka NZisserman AEichner MFerrari VJawahar CIp HRui Y(2012)Video retrieval by mimicking posesProceedings of the 2nd ACM International Conference on Multimedia Retrieval10.1145/2324796.2324838(1-8)Online publication date: 5-Jun-2012
https://dl.acm.org/doi/10.1145/2324796.2324838
Chacon-Murguia MUrias-Zavala J(2012)A comparison between a DTCNN and SOM like approach for dynamic object detection in videos2012 Annual Meeting of the North American Fuzzy Information Processing Society (NAFIPS)10.1109/NAFIPS.2012.6291048(1-6)Online publication date: Aug-2012
https://doi.org/10.1109/NAFIPS.2012.6291048
Show More Cited By

Index Terms

Video parsing based on head tracking and face recognition
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Computer vision problems
        Object recognition

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Published In

cover image ACM Conferences

CIVR '07: Proceedings of the 6th ACM international conference on Image and video retrieval

July 2007

655 pages

ISBN:9781595937339

DOI:10.1145/1282280

General Chairs:
Nicu Sebe
Univ. of Amsterdam, The Netherlands
,
Marcel Worring
Univ. of Amsterdam, The Netherlands

Copyright © 2007 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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SIGMM: ACM Special Interest Group on Multimedia

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SIGIR: ACM Special Interest Group on Information Retrieval

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Association for Computing Machinery

New York, NY, United States

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Published: 09 July 2007

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CIVR07: International Conference on Image and Video Retrieval 2007

July 9 - 11, 2007

Amsterdam, The Netherlands

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Cited By

Chacon-Murguia MUrias-Zavala D(2014)A DTCNN Approach on Video Analysis: Dynamic and Static Object SegmentationRecent Advances on Hybrid Approaches for Designing Intelligent Systems10.1007/978-3-319-05170-3_22(315-336)Online publication date: 27-Mar-2014
https://doi.org/10.1007/978-3-319-05170-3_22
Jammalamadaka NZisserman AEichner MFerrari VJawahar CIp HRui Y(2012)Video retrieval by mimicking posesProceedings of the 2nd ACM International Conference on Multimedia Retrieval10.1145/2324796.2324838(1-8)Online publication date: 5-Jun-2012
https://dl.acm.org/doi/10.1145/2324796.2324838
Chacon-Murguia MUrias-Zavala J(2012)A comparison between a DTCNN and SOM like approach for dynamic object detection in videos2012 Annual Meeting of the North American Fuzzy Information Processing Society (NAFIPS)10.1109/NAFIPS.2012.6291048(1-6)Online publication date: Aug-2012
https://doi.org/10.1109/NAFIPS.2012.6291048
Fischer MEkenel HStiefelhagen R(2011)Person re-identification in TV series using robust face recognition and user feedbackMultimedia Tools and Applications10.1007/s11042-010-0603-255:1(83-104)Online publication date: 1-Oct-2011
https://dl.acm.org/doi/10.1007/s11042-010-0603-2
Xi Li Weiming Hu Zhongfei Zhang Hanzi Wang (2010)Heat Kernel Based Local Binary Pattern for Face RepresentationIEEE Signal Processing Letters10.1109/LSP.2009.203665317:3(308-311)Online publication date: Mar-2010
https://doi.org/10.1109/LSP.2009.2036653
Fischer MEkenel HStiefelhagen R(2010)Interactive person re-identification in TV series2010 International Workshop on Content Based Multimedia Indexing (CBMI)10.1109/CBMI.2010.5529898(1-6)Online publication date: Jun-2010
https://doi.org/10.1109/CBMI.2010.5529898
Sivic JEveringham MZisserman A(2009)“Who are you?” - Learning person specific classifiers from video2009 IEEE Conference on Computer Vision and Pattern Recognition10.1109/CVPR.2009.5206513(1145-1152)Online publication date: Jun-2009
https://doi.org/10.1109/CVPR.2009.5206513
Ferrari VMarin-Jimenez MZisserman A(2009)Pose search: Retrieving people using their pose2009 IEEE Conference on Computer Vision and Pattern Recognition10.1109/CVPR.2009.5206495(1-8)Online publication date: Jun-2009
https://doi.org/10.1109/CVPR.2009.5206495

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