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SPIE Conference on Intelligent Robots and Computer Vision XXVI: Algorithms and Techniques, San Jose, CA, January 2009

This research was conducted at the Fordham University Robotics and Computer Vision Lab. For more information about graduate programs in Computer Science, see http://www.cis.fordham.edu/graduate.html, and the Fordham University Graduate School of Arts and Sciences, see http://www.fordham.edu/gsas.

Disciplines

Computer Engineering | Robotics

Abstract

A mobile robot moving in an environment in which there are other moving objects and active agents, some of which may represent threats and some of which may represent collaborators, needs to be able to reason about the potential future behaviors of those objects and agents. In this paper we present an approach to tracking targets with complex behavior, leveraging a 3D simulation engine to generate predicted imagery and comparing that against real imagery. We introduce an approach to compare real and simulated imagery and present results using this approach to locate and track objects with complex behaviors. In this approach, the salient points in real and imaged images are identified and an affine image transformation that maps the real scene to the synthetic scene is generated. An image difference operation is developed that ensures that the matched points in both images produce a zero difference. In this way, synchronization differences are reduced and content differences enhanced. A number of image pairs are processed and presented to illustrate the approach.

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