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Michael Dixon

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4 papers

2 author rows

IROS Conference 2007 Conference Paper

Faster and more accurate face detection on mobile robots using geometric constraints

Michael Dixon
Frederick Heckel
Robert Pless
William D. Smart

We develop a framework to allow generic object detection algorithms to exploit geometric information commonly available to robot vision systems. Robot systems take pictures with calibrated cameras from known positions and may simultaneously capture depth measurements in the scene. This allows known constraints on the 3D size and position of objects to be translated into constraints on potential locations and scales of objects in the image, eliminating potentially expensive image operations for geometrically infeasible object locations. We show this integration to be very natural in the context of face detection and find that the computational effort of the standard Viola Jones face detector (as implemented in OpenCV) can be reduced by 85 percent with three times fewer false positives.

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IROS Conference 2003 Conference Paper

An autonomous robot photographer

Zachary Byers
Michael Dixon
Kevin Goodier
Cindy M. Grimm
William D. Smart

We describe a complete, end-to-end system for taking well-composed photographs using a mobile robot. The general scenario is a reception, or other event, where people are roaming around talking to each other. The robot serves as an "event photographer", roaming around the same space as the participants, periodically taking photographs. These images are then sent to a workstation where participants can print the photographs out, or email them.

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NMR Workshop 1989 Conference Paper

Massively Parallel Assumption-Based Truth Maintenance

Michael Dixon
Johan de Kleer

Abstract De Kleer's Assumption-based Truth Maintenance System (ATMS) is a propositional inference engine designed to simplify the construction of problem solvers that search complex search spaces efficiently. The ATMS has become a key component of many problem solvers, and often the primary consumer of computational resources. Although considerable effort has gone into designing and optimizing the Lisp implementation, it now appears to be approaching the performance limitations of serial architectures. In this paper we show how the combination of a conventional serial machine and a massively parallel processor can dramatically speed up the ATMS algorithms, providing a very powerful general purpose architecture for problem solving.

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AAAI Conference 1988 Conference Paper

Massively Parallel Assumption-Based Truth Maintenance

Michael Dixon

De Kleer’ s Assumption-based Truth Maintenance System (ATMS) is a propositional inference engine designed to simplify the construction of problem solvers that search complex search spaces efficiently. The ATMS has become a key component of many problem solvers, and often the primary consumer of computational resources. Although considerable effort has gone into designing and optimizing the LISP implementation, it now appears to be approaching the performance limitations of serial architectures. In this paper we show how the combination of a conventional serial machine and a massively parallel processor can dramatically speed up the ATMS algorithms, providing a very power&l general purpose architecture for problem solving.

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