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Semiorder Database for Complex Activity Recognition in Multi-Sensory Environments
San Diego, California February 28-March 03
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICDE.2000.83949616th International Conference on Data ...
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Shailendra Bhonsle, University of California at San Diego
Amarnath Gupta, University of California at San Diego
Simone Santini, University of California at San Diego
Ramesh Jain, University of California at San Diego
A prototype semiorder database used for activity recognition in multi-sensory monitoring environments is described. Activities are spatio-temporal compositions of events, which are a type of atomic semantic units for such compositions. The focus is on the temporal composition of activities from events in the presence of bounded duration of temporal uncertainty in an event occurrence. Such temporal uncertainty forces the concurrency between event occurrences to be intransitive. Under certain assumptions, a subclass of partial orders, known as semiorders, models such intransitive concurrency appropriately.The semiorder database stores events and their semiorder temporal order of occurrences. A semiorder data model and the corresponding query language that embeds a semiorder pattern language are the main constituents of the semiorder database. We demonstrate this database and queries for activity recognition in a real time environment. The demonstration also includes a transducer subsystem for detection of events.
Index Terms:
Semiorder database, semiorders, database, event, activity, semiorder composition
Citation:
Shailendra Bhonsle, Amarnath Gupta, Simone Santini, Ramesh Jain, "Semiorder Database for Complex Activity Recognition in Multi-Sensory Environments," icde, pp.689, 16th International Conference on Data Engineering (ICDE'00), 2000
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