Skip to main content
SpringerLink
Log in

Automatic video object generation tool: segmentation and tracking of persons in real time

Un outil de génération automatique d’objet vidéo : Segmentation et suivi de personnes en temps réel

  • Published:
Annales Des Télécommunications Aims and scope Submit manuscript

Abstract

In the field of the multimedia applications, future standards as mpeg4 or mpeg7 allow new image content representation that goes far from the basic compression. This way, the objects of interest become entities that the user can manipulate. Nevertheless, the norm does not specify how objects have to be segmented, even if in some cases this is a complex task. In the framework of the European project m4m (mpeg fo(u)r Mobiles, Medea project Al 16), we have in charge the development of a demonstrator able to segment and track a speaker in videophone and vidéoconférence applications.

Résumé

Dans le domaine des applications multimédias, les futures normes telles que mpeg4 ou mpeg7 permettent des représentations élaborées du contenu des images, qui vont bien au-delà de la simple compression. Ainsi, les objets d’intérêt dans la scène deviennent des entités que l’utilisateur peut manipuler. Néanmoins, la norme ne spécifie pas comment les objets doivent être segmentés, même si dans certains cas cette tâche est extrêmement complexe. Dans le cadre du projet européen m4m (mpeg fo(u)r mobiles, Medea projet Al 16), un démonstrateur capable de segmenter a été développé et le locuteur a été suivi dans des applications de visiophonie ou de vidéoconférence.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Marques (F.), Llach (J). Tracking of generic objects for video object generation.Proceedings of the International Conference on Image Processing, ICIP, Chicago, 1998.

    Google Scholar 

  2. Gatica-Perez (D.), Sun (M.), Gu (C). Semantic video object extraction based on backward tracking of multivalued watershed.International Conference on Image Processing, ICIP. (1999).

  3. Marcotegui (B.), Correirea (P.), Marques (F.), Merch (R.), Rosa (R.), Wollborn (M.), Zanoguera (F.). Vogue: the MoMuSys video object generator with user environment.Workshop on Image Analysis for Multimedia Interactive Services, WIAMIS. Berlin, (1999), pp. 25–28.

    Google Scholar 

  4. Papageorgiou (C), Oren (M.), Poggio (T.). A general framework for object detection.Proceedings of International Conference on Computer Vision. Bombay, India (1998).

  5. Meier (T.), Ngan (K.N.). Automatic segmentation of moving objects for video object plane generation.IEEE Trans. on Circuits and Systems for Video Technology, (1998),8, n°. 5, pp. 525–538.

    Article  Google Scholar 

  6. Chellapa (R.), Wilson (C), Sirohey (S.). Human and machine recognition of faces: a survey.Proceedings of the IEEE. (1995),83, n° 5, pp. 705–740.

    Article  Google Scholar 

  7. Abdel-Mottaleb (M.), Elgammal (A.). Face detection in Complex Environments from color images,International Conference on Image Processing, ICIP. (1999).

  8. Terrillon (J.C.), Akamatsu (S.). Comparative performance of different chrominance spaces for color segmentation and detection of human faces in complex scene images.Vision Interface, Canada, (1999).

  9. Beucher (S.), Meyer (F.). The morphological approach to segmentation: the watershed transformation, in E. Dougherty (ed.), Mathematical Morphology in Image Processing, New York,M. Dekker, (1993), Chapter 12, pp. 433–481.

    Google Scholar 

  10. Sabottka (K.), Pitas (I.). A novel method for automatic face segmentation, facial feature extraction and tracking.Signal Processing: Image Communication. (1998)12, pp. 263–281.

    Article  Google Scholar 

  11. Meyer (F.). From connected operators to levelings.Mathematical Morphology and its Applications to Image and Signal Processing, ICMM’98. Amsterdam, (1998), pp.191–199.

  12. Meyer (F.). The levelings. In H. Heijmans and J. Roerdink (Ed.),Mathematical Morphology and its Applications to Image and Signal Processing, Kluwer (1998), pp. 199–207.

  13. Meyer (F.). Graph based morphological segmentation, “2ndIAPR-TC-15 Workshop on Graph-based representation”, OCG Schriftenreihe, to appear december 1999.

  14. Vachier (C), Extraction de caractéristiques, segmentation d’image et morphologie mathématique.Ph.D. thesis, Ecole des Mines de Paris, (1995).

Download references

Author information

Authors and Affiliations

  1. Ecole des Mines de Paris, Centre de Morphologie Mathématique, 35 rue Saint-Honoré, F-77305, Fontainebleau, France

    Cristina Gomila & Fernand Meyer

Authors
  1. Cristina Gomila
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Fernand Meyer
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding authors

Correspondence to Cristina Gomila or Fernand Meyer.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Gomila, C., Meyer, F. Automatic video object generation tool: segmentation and tracking of persons in real time. Ann. Télécommun. 55, 172–183 (2000). https://doi.org/10.1007/BF03001910

Download citation

  • Received:

  • Accepted:

  • Issue Date:

  • DOI: https://doi.org/10.1007/BF03001910

Key words

Mots clés

Search

Navigation