Spatio-temporal Modeling of Moving Objects for Content- and Semantic-Based Retrieval in Video Data

Abstract

The general aim of this paper is to study the spatio-temporal representation scheme which can efficiently model moving objects’ trajectories in video data. Our scheme deals with not only the single moving object but the multiple (two or more) moving objects. The traditional schemes only consider direction property, time interval property, and spatial relationship property for modeling moving objects’ trajectories. But, our scheme also takes into account on distance property, conceptual location information, and related object information (e.g. player name having a soccer ball) so that we may improve a retrieval accuracy to measure a similarity between two moving objects as well as them. The proposed spatio-temporal representation scheme supports content-based retrieval using moving objects’ trajectories and supports semantics-based retrieval using concepts which are acquired through the conceptual location information of moving objects. Finally, we show from our experiment that our scheme is superior to existing related work about 10-20% in terms of retrieval effectiveness.