The ThreadMill architecture for stream-oriented human communication analysis applications

  • Authors:
  • Paulo Barthelmess;Clarence A. Ellis

  • Affiliations:
  • University of Colorado at Boulder, Boulder, CO;University of Colorado at Boulder, Boulder, CO

  • Venue:
  • Proceedings of the 6th international conference on Multimodal interfaces
  • Year:
  • 2004

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Abstract

This work introduces a new component software architecture - ThreadMill - whose main purpose is to facilitate the development of applications in domains where high volumes of streamed data need to be efficiently analyzed. It focuses particularly on applications that target the analysis of human communication e.g. in speech and gesture recognition. Applications in this domain usually employ costly signal processing techniques, but offer in many cases ample opportunities for concurrent execution in many different phases. ThreadMill's abstractions facilitate the development of applications that take advantage of this potential concurrency by hiding the complexity of parallel and distributed programming. As a result, ThreadMill applications can be made to run unchanged on a wide variety of execution environments, ranging from a single-processor machine to a cluster of multi-processor nodes. The architecture is illustrated by an implementation of a tracker for hands and face of American Sign Language signers that uses a parallel and concurrent version of the Joint Likelihood Filter method.