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Proceedings Paper

A relaxed fusion of information from real and synthetic images to predict complex behavior
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Paper Abstract

An important component of cognitive robotics is the ability to mentally simulate physical processes and to compare the expected results with the information reported by a robot's sensors. In previous work, we have proposed an approach that integrates a 3D game-engine simulation into the robot control architecture. A key part of that architecture is the Match-Mediated Difference (MMD) operation, an approach to fusing sensory data and synthetic predictions at the image level. The MMD operation insists that simulated and predicted scenes are similar in terms of the appearance of the objects in the scene. This is an overly restrictive constraint on the simulation since parts of the predicted scene may not have been previously viewed by the robot. In this paper we propose an extended MMD operation that relaxes the constraint and allows the real and synthetic scenes to differ in some features but not in (selected) other features. Image difference operations that allow a real image and synthetic image generated from an arbitrarily colored graphical model of a scene to be compared. Scenes with the same content show a zero difference. Scenes with varying foreground objects can be controlled to compare the color, size and shape of the foreground.

Paper Details

Date Published: 6 June 2011
PDF: 8 pages
Proc. SPIE 8064, Multisensor, Multisource Information Fusion: Architectures, Algorithms, and Applications 2011, 806409 (6 June 2011); doi: 10.1117/12.886014
Show Author Affiliations
Damian M. Lyons, Fordham Univ. (United States)
D. Paul Benjamin, Pace Univ. (United States)


Published in SPIE Proceedings Vol. 8064:
Multisensor, Multisource Information Fusion: Architectures, Algorithms, and Applications 2011
Jerome J. Braun, Editor(s)

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