A SYNTACTIC METHOD FOR TIME-VARYING PATTERN ANALYSIS

TZU-I JONATHAN FAN, Purdue University

Abstract

A syntactic method for the analysis of time-varying image patterns is proposed and studied. This method utilizes translation schema to model the time-varying properties of image patterns. A syntactic deformation model is first applied to transform the i-th image into the (i+1)-th image of an image sequence. Then the concept of translation in formal language theory is used as a mechanism to characterize the dynamic process of the image sequence. A formulation of stochastic translation is also presented. A generalized syntax-directed tree translation model is proposed to handle high-dimensional patterns. The generalized model is compared with the conventional top-down and bottom-up tree translation models. A traffic monitoring problem is analyzed using the proposed tree translation model. Each input image is represented as a tree structure. The proposed tree translation model is used to model the variation of image content between consecutive images. A parsing algorithm for tree translation is applied to match moving objects (vehicles) in each pair of consecutive images.

Degree

Ph.D.

Subject Area

Electrical engineering

Off-Campus Purdue Users:
To access this dissertation, please log in to our
proxy server
.

Share

COinS