VisQuery: Visual querying of streaming data via pattern matching

Chenhui Li, George Baciu, Yunzhe Wang

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review


Querying streaming data is becoming a dominant problem in big data analytics. A practical approach to querying streaming data is through traditional databases that have been modified to support streams, such as MySQL. However, conditional selection for querying data streams is currently an open challenge. We present a new visual framework that provides a more intuitive querying interaction for streaming data by combining visual selections on patterns with image processing techniques in order to better identify regions of interest. The main contribution of this paper is a novel method for matching patterns among normalized frames via feature vector clustering.
Original languageEnglish
Title of host publication2016 Digital Media Industry and Academic Forum, DMIAF 2016 - Proceedings
Number of pages5
ISBN (Electronic)9781509010004
Publication statusPublished - 22 Sep 2016
Event2016 Digital Media Industry and Academic Forum, DMIAF 2016 - Santorini, Greece
Duration: 4 Jul 20166 Jul 2016


Conference2016 Digital Media Industry and Academic Forum, DMIAF 2016

ASJC Scopus subject areas

  • Computer Science Applications
  • Media Technology

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