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HONS 03/07

Tracking Object Trajectories Relative to Planar Surfaces Using Stereo

Matthew Elliot
Department of Computer Science
University of Canterbury

Abstract

This project proposes a methodology for 3D tracking of objects in relation to a planar surface, with trajectory accuracy enhanced using applied statistical analysis. Planar surface extraction, with camera position and orientation invariance, is achieved by finding limiting regions established by graph-based segmentation and mapping the resulting segments to disparity data from a stereo camera. Secondly, object detection and tracking is performed using a combination of adaptive background subtraction and least squares linear regression for calculating object trajectories. The accuracy of bounding planar surface extraction is shown to be accurate to within 1.4% and tracking has shown similar high correlations between the calculated and actual positions.