ZatLab: gesture recognition framework for artistic performance interaction - overview

André Baltazar, Luís Gustavo Martins

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


The main problem this paper 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. Therefore, this paper describes a gesture recognition framework developed with the goal of being used mainly in artistic performance domain. First one will review the previous works done in the area, followed by the description of the framework design and there is also the review of two artistic applications of the framework. The overall goal of this research is to foster the use of gestures, in an artistic context, to the creation of new ways of expression.
Original languageEnglish
Title of host publicationProceedings of 7th international conference on digital arts
EditorsJosé Bidarra, Teresa Eça, Mírian Tavares, Rosangella Leote, Lucia Pimentel, Elizabeth Carvalho, Mauro Figueiredo
PublisherArtech International Association
Number of pages4
ISBN (Electronic)9789899937000
Publication statusPublished - 2015
Event7th International Conference on Digital Arts (ARTECH) - Óbidos, Portugal
Duration: 19 Mar 201520 Mar 2015


Conference7th International Conference on Digital Arts (ARTECH)


  • HCI
  • Gesture recognition
  • Machine learning
  • Interactive performance


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