Video retrieval using successive modular operations on temporal similarity

Abstract

A video retrieval system consists of two major subsystems for indexing and querying, respectively. In this paper, we propose a framework for retrieving video sequences using modular operations on temporal similarity. In the indexing process, the contents (objects) of a video sequence are used to build temporal triples representing temporal relationships between objects. For every temporal triple generated from different video sequences, a prime number is assigned to it by the proposed prime number assignment (PNA) algorithm. For each video sequence, a standing value is generated via its set of prime numbers. In the query process, successive modular operations (SMO) on the standing values are used to retrieve video sequences. Based on the PNA and the SMO, we built an experimental video retrieval system. From the simulation results, we notice that a query can be done in a linear time.