Indexing Large Video Databases to Support Efficient Query Processing (2015–2017)

This project aims at developing breakthrough database technology that leverages the advances in video data capturing, computer vision based object recognition, multimedia tagging, large scale database systems and parallel processing, to provide the capability of managing massive video data with enriched semantic information and enabling database-like flexible and efficient video information search. It will establish a new data management and processing foundation for big video data analytics.
Grant type:
ARC Discovery Projects
  • Professor
    School of Information Technology and Electrical Engineering
    Faculty of Engineering, Architecture and Information Technology
Funded by:
Australian Research Council