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A shared parameter model for gesture and sub-gesture analysis

  • SUNY Buffalo

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

6 Scopus citations

Abstract

Gesture sequences typically have a common set of distinct internal sub-structures which can be shared across the gestures. In this paper, we propose a method using a generative model to learn these common actions which we refer to as sub-gestures, and in-turn perform recognition. Our proposed model learns sub-gestures by sharing parameters between gesture models. We evaluated our method on the Palm Graffiti digits-gesture dataset and showed that the model with shared parameters outperformed the same model without the shared parameters. Also, we labeled different observation sequences thereby intuitively showing how sub-gestures are related to complete gestures.

Original languageEnglish
Title of host publicationCombinatorial Image Analysis - 14th International Workshop, IWCIA 2011, Proceedings
Pages483-493
Number of pages11
DOIs
StatePublished - 2011
Event14th International Workshop on Combinatorial Image Analysis, IWCIA 2011 - Madrid, Spain
Duration: May 23 2011May 25 2011

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6636 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference14th International Workshop on Combinatorial Image Analysis, IWCIA 2011
Country/TerritorySpain
CityMadrid
Period05/23/1105/25/11

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