Integrating declarative models and HMMs for online gesture recognition

Carcangiu A.;Spano L. D.
2019-01-01

Abstract

In the last years, the introduction of new, precise and pervasive tracking devices has contributed to the popularity of gestural interaction. In general, the effectiveness of such interfaces depends on two components: the algorithm used for accurately recognizing the user movements and the guidance provided to users while executing gestures. In this paper, we discuss a work in progress research for connecting these two components and increasing their effectiveness: the recognition algorithm supports the implementation of feedback the and feed-forward mechanisms, providing information on the identified gesture parts in real time, while developers define complex gestures starting from simple primitives.
2019
9781450366731
compositional gesture modelling; feedback; feedforward; gestures; hidden Markov models; online recognition
Files in This Item:
File Size Format  
paper.pdf

Solo gestori archivio

Type: versione pre-print
Size 604.39 kB
Format Adobe PDF
604.39 kB Adobe PDF & nbsp; View / Open   Request a copy

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.

Questionnaire and social

Share on:
Impostazioni cookie