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Evaluation of unsupervised segmentation algorithms for silhouette extraction in human action video sequences

  • Adolfo Martinez-Uso
  • , G. Salgues
  • , S.A. Velastin
  • Jaume I University
  • Université de Strasbourg
  • Kingston University

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The main motivation of this work is to find and evaluate solutions for generating binary masks (silhouettes) of foreground targets in an automatic way. To this end, four renowned unsupervised image segmentation algorithms are applied to foreground segmentation. A comparison among these algorithms is carried out using the MuHAVi dataset of multi-camera human action video sequences. This dataset presents significant challenges in terms of harsh illumination resulting for example in high contrast and deep shadows. The segmentation results have been objectively evaluated against manually derived ground-truth silhouettes.
Original languageEnglish
Title of host publicationVisual informatics
Subtitle of host publicationsustaining research and innovations
EditorsH.B. Zaman, P. Robinson, M. Petrou, P. Olivier, T. K. Shih, S. Velastin, I. Nyström
Place of PublicationBerlin, Germany
PublisherSpringer
Pages13-22
Number of pages10
Volume7066
ISBN (Electronic)9783642251917
ISBN (Print)9783642251900
DOIs
Publication statusPublished - Nov 2011
Externally publishedYes
EventSecond International Visual Informatics Conference - Selangor, Malaysia
Duration: 9 Nov 201111 Nov 2011

Publication series

NameLecture Notes in Computer Science
PublisherSpringer
Volume7066
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

ConferenceSecond International Visual Informatics Conference
Period9/11/1111/11/11

Bibliographical note

Organising Body: Springer

Keywords

  • Computer science and informatics

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