Repository logo
 
Publication

ZatLab gesture recognition framework: machine learning results

2016Journal article Restricted access
Simple item page
dc.contributor.authorBaltazar, André
dc.date.accessioned2017-11-13T15:57:43Z
dc.date.available2017-11-13T15:57:43Z
dc.date.issued2016
dc.description.abstractThe main problem this work addresses is the real-time recognition of gestures, particularly in the complex domain of artistic performance. By recognizing the performer gestures, one is able to map them to diverse controls, from lightning control to the creation of visuals, sound control or even music creation, thus allowing performers real-time manipulation of creative events. The work presented here takes this challenge, using a multidisciplinary approach to the problem, based in some of the known principles of how humans recognize gesture, together with the computer science methods to successfully complete the task. This paper is a consequence of previous publications and presents in detail the Gesture Recognition Module of the ZatLab Framework and results obtained by its Machine Learning (ML) algorithms. One will provide a brief review the previous works done in the area, followed by the description of the framework design and the results of the recognition algorithms.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationBaltazar, A. (2016). ZatLab Gesture Recognition Framework: Machine Learning Results. International Journal of Creative Interfaces and Computer Graphics, (7)2, 11-24pt_PT
dc.identifier.doi10.4018/IJCICG.2016070102pt_PT
dc.identifier.issn1947-3117
dc.identifier.urihttp://hdl.handle.net/10400.14/23350
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.subjectComputer Visionpt_PT
dc.subjectDTWpt_PT
dc.subjectGesture Recognitionpt_PT
dc.subjectHCIpt_PT
dc.subjectHMMpt_PT
dc.subjectInteractive Performancept_PT
dc.subjectKinectpt_PT
dc.subjectMachine Learningpt_PT
dc.titleZatLab gesture recognition framework: machine learning resultspt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.citation.titleInternational Journal of Creative Interfaces and Computer Graphicspt_PT
person.familyNameBaltazar
person.givenNameAndré
person.identifier.orcid0000-0003-4047-1395
rcaap.rightsrestrictedAccesspt_PT
rcaap.typearticlept_PT
relation.isAuthorOfPublication58aee589-e111-4f5d-9dbb-80efcd52f29b
relation.isAuthorOfPublication.latestForDiscovery58aee589-e111-4f5d-9dbb-80efcd52f29b

Files

Original bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
ZatLab-Gesture-Recognition-Framework_-Machine-Learning-Results-2.pdf
Size:
581.35 KB
Format:
Adobe Portable Document Format
Download
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
3.44 KB
Format:
Item-specific license agreed upon to submission
Description:
Download

Collections

CITAR - Contribuições em Revistas Científicas / Contribution to Journals