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Proceedings Paper

Semi-automatic image segmentation and object tracking framework for investigative and surveillance-oriented applications
Author(s): Patrick De Smet; Ignace Bruyland
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Paper Abstract

In this paper we discuss a combination of several image processing and computer vision components for the purpose of semi-automatically delineating and tracking moving objects. First, we introduce our motion based segmentation framework which uses an improved watershed technique to obtain an image pre-segmentation, and an improved block or segment matching technique to obtain an initial estimation of the motion field. The initial pre-segmentation and motion estimation results are then fed into an additional component which reduces the typical watershed oversegmentation until only a few coherently moving objects remain. Next, we discuss two tools that can be used to improve or correct the obtained segmentation results. Also, we investigate a simple, yet efficient object oriented approach for tracking moving segments; we discuss the concept of truncated segment matching, which combines characteristics of both traditional block matching and feature based motion estimation processes. Additionally, we use polynomial motion models to describe and predict the observed motion. The proposed segment matching approach is shown to allow controllable and relatively fast computation, which is illustrated with image segmentation and video tracking results. Finally, we briefly discuss the use of these techniques within the domain of investigative and surveillance oriented applications.

Paper Details

Date Published: 19 July 2002
PDF: 12 pages
Proc. SPIE 4709, Investigative Image Processing II, (19 July 2002); doi: 10.1117/12.474736
Show Author Affiliations
Patrick De Smet, Ghent Univ. (Belgium)
Ignace Bruyland, Ghent Univ. (Belgium)

Published in SPIE Proceedings Vol. 4709:
Investigative Image Processing II
Zeno J. Geradts; Lenny I. Rudin, Editor(s)

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