While a query result in a traditional database is a subset of the
database, in a video database, it is a set of subintervals extracted
from the raw video sequence. It is very hard, if not impossible, to
predetermine all the queries that will be issued in future, and all
the subintervals that will become necessary to answer them. As a
result, conventional query frameworks are not applicable to video
databases. In this paper, we propose a new video query model that
computes query results by dynamically synthesizing needed subintervals
from fragmentary indexed intervals in the database. We introduce new
interval operations required for that computation. We also propose
methods to compute relative relevance of synthesized intervals to a
given query. A query result is a list of synthesized intervals sorted
in the order of their degree of relevance.
video database, video retrieval, video query, interval operations,
video indexing, ranking method, interval query semantics, query
approximation
In IEEE Trans. on Knowledge and Data Eng., Vol.13, No.5, pp.824-838, Sept./Oct. 2001
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