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VISLab
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University of California, Riverside
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IEEE Biometrics Workshop 2019
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Last updated: July 1, 2017

An Integrated Approach for Query, Indexing and Retrieval of Spatio-Temporal Data

Presented by: sohail Nadimi

Abstract : It has been shown that a typical Relational or Object database system can not easily and efficiently handle new data types such as Image, Voice, Video, etc. , unless its capabilities have been extended. Video data in particular is of spatio-temporal nature. Objects (subjects) in video have spatial relationships and viewed in different frames have temporal relationships. For example, a picture depicting a man standing on a bridge, shows exactly that; however, a video clip may reveal a lot more information such as where the man has been, where he is heading for, what direction, how he got to that point on the bridge and possibly how long he spent on the bridge to name a few.
Since Video data is spatio-temporal in nature, it provides a good test bed for research in the spatio-temporal database systems.

In this talk I will present bulk of research that has been done in the Video database management systems. Areas covered are : Queries, Data Modeling, Indexing

This research is from two different perspectives, the AI/Computer Vision/Image Processing,... and the Theoretical/Mathematical and analytical data management perspective. The two components , Video Processing and Database & data management are both important, yet no researcher has looked at both issues simultaneously. In conclusion, a roadmap for research in this domain is provided.