KIND-DAMA: a Middleware for Kinect-like Devices and Data Management

Project Info

Project Description

Nowadays, gestural input is considered one of the most promising solution for seamless interactions between humans and digital artifacts available in their surrounding environment. Among other reasons, this is also due to the large availability of different low-cost gesture acquisition hardware (the so-called “Kinect-like devices”). As a consequence, there is a growing need for solutions that allows for an easy integration of such devices within actual systems.

This project consists in a modular open middleware to be used in the development of systems based on gestural input (namely KIND-DAMA). The work made by USI group consists in the design of its architecture, its implementation and the related evaluation in real use cases.

The source code of KIND-DAMA is publicly available on GitHub; a link to the repository is provided at the end of this page.



  • [DOI] F. Milazzo, V. Gentile, A. Gentile, and S. Sorce, “KIND-DAMA: A modular middleware for Kinect-like device data management,” Software: practice and experience, vol. 48, iss. 1, pp. 141-160, 2018.
    author = {Fabrizio Milazzo and Vito Gentile and Antonio Gentile and Salvatore Sorce},
    title = {{KIND-DAMA: A modular middleware for Kinect-like device data management}},
    journal = {Software: Practice and Experience},
    volume = {48},
    number = {1},
    issn = {1097-024X},
    url = {},
    doi = {10.1002/spe.2521},
    pages = {141--160},
    keywords = {gestural data management, gesture interaction middleware, Kinect-like devices},
    year = {2018}
  • [PDF] [DOI] F. Milazzo, V. Gentile, S. Sorce, G. Vitello, and A. Gentile, “Modular Middleware for Gestural Data and Devices Management,” Journal of Sensors, vol. 2017, 2017.
    title = {{Modular Middleware for Gestural Data and Devices Management}},
    author = {Fabrizio Milazzo and Vito Gentile and Salvatore Sorce and Giuseppe Vitello and Antonio Gentile},
    journal = {{Journal of Sensors}},
    url = {},
    year = {2017},
    numpages = {13},
    volume = 2017,
    doi = {10.1155/2017/9196070}