Continuous acoustic source tracking for tangible acoustic interfaces

Ming Yang, M. Al-Kutubi, D.T. Pham

    Research output: Contribution to journalArticle

    6 Citations (Scopus)


    The challenge in human computer interaction is to create tangible interfaces that will make digital world accessible through augmented physical surfaces like walls and windows. In this paper, two continuous acoustic source tracking methods are proposed which have the potential to covert a physical object into a tracking sensitive interface. The spatial likelihood method has been used to locate an acoustic source in real time. The source location is obtained from searching the maximum in the likelihood map. The Kalman filter is used to improve the trajectory estimation by predicting the location based on the previous source location and the current measurement of the source location. Finally a Linear Positioning algorithm is proposed for acoustic source tracking. This method is independent on the spatial size of the tangible object and thus applicable on large interactive surfaces without additional computation cost. Promising results have been achieved experimentally for the application of acoustic tangible interfaces.
    Original languageEnglish
    Pages (from-to)1272-1278
    Issue number3
    Publication statusPublished - 2013

    Bibliographical note

    The full text of this item is not currently available from the repository.
    NOTICE: this is the author’s version of a work that was accepted for publication in Measurement. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Measurement [Vol 46, Issue 3, (2013)] DOI: 10.1016/j.measurement.2012.11.019


    European FP6 IST Project


    • acoustic source localization
    • acoustic source tracking
    • multi-sensor data fusion
    • time-difference-of-arrival


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