skip to main content
10.1145/1743384.1743435acmconferencesArticle/Chapter ViewAbstractPublication PagesmmConference Proceedingsconference-collections
poster

Face-and-clothing based people clustering in video content

Published: 29 March 2010 Publication History

Abstract

Content-based people clustering is a crucial step for people indexing within video documents. In this paper, we investigate the use of both face and clothing features. A method of extracting a keyface for each video sequence is proposed. An algorithm based on the average of the N-minimum pair distances between local invariant features is used in order to resolve the problem of face matching. An original method for clothing matching is proposed based on 3D histogram of the dominant color. A 3-levels hierarchical bottom-up clustering that combines local invariant features, skin color, 3D histogram and clothing texture is also described. Experiments and results show the efficiency of the proposed clustering system.

References

[1]
O. Arandjelovic and A. Zisserman. Automatic face recognition for film character retrieval in feature-length films. CVPR'05: Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, volume 1, pages 860--867. IEEE Computer Society, 2005.
[2]
J. S. Beis and D. G. Lowe. Shape indexing using approximate nearest-neighbour search in high-dimensional spaces. Proc. IEEE Conf. Comp. Vision Patt. Recog, pages 1000--1006, 1997.
[3]
P. N. Belhumeur, J. P. Hespanha, J. ao P. Hespanha, and D. J. Kriegman. Eigenfaces vs. fisherfaces: Recognition using class specific linear projection. IEEE Transactions on Pattern Analysis and Machine Intelligence, 19:711--720, 1996.
[4]
M. Bicego, A. Lagorio, E. Grosso, and M. Tistarelli. On the use of sift features for face authentication. Computer Vision and Pattern Recognition Workshop, 2006. CVPRW'06., pages 35--41, June 2006.
[5]
S.-F. Chang, J. He, Y.-G. Jiang, E. El Khoury, C.-W. Ngo, A. Yanagawa, and E. Zavesky. Columbia University/VIREO-CityU/IRIT TRECVID2008 High-Level Feature Extraction and Interactive Video Search. TREC Video Retrieval Workshop (TRECVID), NIST in Gaithersburg, MD. NIST, 2008.
[6]
E. El-Khoury, C. Senac, and J. Pinquier. Improved speaker diarization system for meetings. IEEE International Conference on Acoustics, Speech, and Signal Processing, pages 4097--4100, 2009.
[7]
M. Everingham, J. Sivic, and A. Zisserman. Hello! my name is... buffy - automatic naming of characters in tv video. Proceedings of the British Machine Vision Conference, BMVC'06, page III:899, 2006.
[8]
A. W. Fitzgibbon and A. Zisserman. On affine invariant clustering and automatic cast listing in movies. ECCV'02: Proceedings of the 7th European Conference on Computer Vision-Part III, pages 304--320, London, UK, 2002. Springer-Verlag.
[9]
S. Haidar, P. Joly, and B. Chebaro. Mining for video production invariants to measure style similarity. International Journal of Intelligent Systems (IJIS), 21(7):747--763, july 2006.
[10]
M. hsuan Yang. Encyclopedia of Biometrics, chapter : Face Detection. Springer, July 2009.
[11]
G. Jaffré and P. Joly. Costume: a New Feature for Automatic Video Content Indexing. RIAO'2004 : Coupling approaches, coupling media and coupling languages for information retrieval, Avignon, pages 314--325. C.I.D., 2004.
[12]
D. G. Lowe. Distinctive image features from scale-invariant keypoints. International Journal of Computer Vision, 60:91--110, 2004.
[13]
S. Maji and R. Bajcsy. Fast unsupervised alignment of video and text for indexing/names and faces. MS'07: Workshop on multimedia information retrieval on The many faces of multimedia semantics, pages 57--64. ACM, 2007.
[14]
B. S. Manjunath and W. Ma. Texture features for browsing and retrieval of image data. IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI) - Special issue on Digital Libraries, 18(8):837--42, Aug 1996.
[15]
A. Martinez and R. Benavente. The AR face database. Technical report, CVC Technical Report, 1998.
[16]
F. Samaria and A. Harter. Parameterisation of a stochastic model for human face identification. WACV'94, pages 138--142, 1994.
[17]
A. F. Smeaton, P. Over, and A. R. Doherty. Video shot boundary detection: Seven years of trecvid activity. Computer Vision and Image Understanding, 2009.
[18]
V. Vezhnevets, V. Sazonov, and A. Andreeva. A survey on pixel-based skin color detection techniques. Proc. Graphicon-2003, pages 85--92, 2003.

Cited By

View all
  • (2024)VideoClusterNet: Self-supervised and Adaptive Face Clustering for VideosComputer Vision – ECCV 202410.1007/978-3-031-73404-5_22(377-396)Online publication date: 30-Oct-2024
  • (2023)Online Multi-Face Tracking With Multi-Modality Cascaded MatchingIEEE Transactions on Circuits and Systems for Video Technology10.1109/TCSVT.2022.322469933:6(2738-2752)Online publication date: Jun-2023
  • (2023)An Analysis of Cultural Content on Short Video Platforms: Cultural Protection PerspectiveE-Business and Telecommunications10.1007/978-3-031-36840-0_2(29-50)Online publication date: 22-Jul-2023
  • Show More Cited By

Recommendations

Comments

Information & Contributors

Information

Published In

cover image ACM Conferences
MIR '10: Proceedings of the international conference on Multimedia information retrieval
March 2010
600 pages
ISBN:9781605588155
DOI:10.1145/1743384

Sponsors

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 29 March 2010

Permissions

Request permissions for this article.

Check for updates

Author Tags

  1. clothing
  2. face
  3. hierarchical clustering
  4. video people indexing

Qualifiers

  • Poster

Conference

MIR '10
Sponsor:
MIR '10: International Conference on Multimedia Information Retrieval
March 29 - 31, 2010
Pennsylvania, Philadelphia, USA

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • Downloads (Last 12 months)3
  • Downloads (Last 6 weeks)0
Reflects downloads up to 21 Jan 2025

Other Metrics

Citations

Cited By

View all
  • (2024)VideoClusterNet: Self-supervised and Adaptive Face Clustering for VideosComputer Vision – ECCV 202410.1007/978-3-031-73404-5_22(377-396)Online publication date: 30-Oct-2024
  • (2023)Online Multi-Face Tracking With Multi-Modality Cascaded MatchingIEEE Transactions on Circuits and Systems for Video Technology10.1109/TCSVT.2022.322469933:6(2738-2752)Online publication date: Jun-2023
  • (2023)An Analysis of Cultural Content on Short Video Platforms: Cultural Protection PerspectiveE-Business and Telecommunications10.1007/978-3-031-36840-0_2(29-50)Online publication date: 22-Jul-2023
  • (2019)Tracking Persons-of-Interest via Unsupervised Representation AdaptationInternational Journal of Computer Vision10.1007/s11263-019-01212-1Online publication date: 3-Sep-2019
  • (2017)Exploiting scene maps and spatial relationships in quasi-static scenes for video face clusteringImage and Vision Computing10.1016/j.imavis.2016.11.00557:C(25-43)Online publication date: 1-Jan-2017
  • (2016)Joint Face Representation Adaptation and Clustering in VideosComputer Vision – ECCV 201610.1007/978-3-319-46487-9_15(236-251)Online publication date: 17-Sep-2016
  • (2014)A conditional random field approach for face identification in broadcast news using overlaid text2014 IEEE International Conference on Image Processing (ICIP)10.1109/ICIP.2014.7025063(318-322)Online publication date: Oct-2014
  • (2014)A conditional random field approach for audio-visual people diarization2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)10.1109/ICASSP.2014.6853569(116-120)Online publication date: May-2014
  • (2014)Finding suits in images of people in unconstrained environmentsJournal of Visual Communication and Image Representation10.1016/j.jvcir.2014.07.00225:7(1588-1594)Online publication date: 1-Oct-2014
  • (2014)Audiovisual diarization of people in video contentMultimedia Tools and Applications10.1007/s11042-012-1080-668:3(747-775)Online publication date: 1-Feb-2014
  • Show More Cited By

View Options

Login options

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Media

Figures

Other

Tables

Share

Share

Share this Publication link

Share on social media