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 the 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.