Primitive human action recognition based on partitioned silhouette block matching

Toru Abe, Masaru Fukushi, Daisuke Ueda

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

This paper deals with the issue of recognizing primitive human actions through template matching with time series silhouette images. Although existing methods based on this simple approach can recognize a subject's action from a low-resolution image sequence, which is a basic requirement for surveillance applications, their recognition accuracy decreases considerably for corrupted silhouettes due to occlusion. To deal with this problem while keeping algorithm simplicity, we propose a novel method, which integrates template matching results for temporally and spatially partitioned silhouette blocks. Experimental results indicate that our method outperforms the existing methods in the accuracy of action recognition for corrupted silhouettes.

Original languageEnglish
Title of host publicationAdvances in Visual Computing - 9th International Symposium, ISVC 2013, Proceedings
Pages308-317
Number of pages10
EditionPART 2
DOIs
Publication statusPublished - 2013 Nov 29
Event9th International Symposium on Advances in Visual Computing, ISVC 2013 - Rethymnon, Crete, Greece
Duration: 2013 Jul 292013 Jul 31

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 2
Volume8034 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other9th International Symposium on Advances in Visual Computing, ISVC 2013
CountryGreece
CityRethymnon, Crete
Period13/7/2913/7/31

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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