General Electric Company

Carnegie Mellon University

Bernardo Pires

Norman Leonard Ovens

José M F Moura

So Young Kim

Michael Eric Figard

Alexander Kaber Carroll

Jennifer Ruth Cooper

Sundar Murugappan

Sharon Ann Green

Masaki Merritt Akiyama

A method of monitoring a cockpit of an aircraft includes receiving, by one or more controllers, an image depicting an operator manipulated input device located within the cockpit. The method can include determining, by the one or more controllers, an observed state of the operator manipulated input device. In particular, the observed state can be based on the image. The method can include determining, by the one or more controllers, a sensed state of the operator manipulated input device. In particular, the sensed state can be based on data from a sensor. The method can include determining, by the one or more controllers, a mismatch between the observed and sensed states of the operator manipulated input device.

System and method for monitoring a cockpit of an aircraft

Feature-matching methods for attempting to match visual features in one image with visual features in another image. Feature-matching methods disclosed progressively sample the affine spaces of the images for visual features, starting with a course sampling and iteratively increasing the density of sampling. Once a predetermined threshold number of unambiguous matches has been satisfied, the iterative sampling and matching can be stopped. The iterative sampling and matching methodology is especially, but not exclusively, suited for use in fully affine invariant feature matching applicants and can be particularly computationally efficient for comparing images that have large differences in observational parameters, such as scale, tilt, object-plane rotation, and image-plane rotation. The feature-matching methods disclosed can be useful in object/scene recognition applications. The disclosed methods can be implemented in software and various object/scene recognition systems.

Systems, methods, and software implementing affine-invariant feature detection implementing iterative searching of an affine space

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Pittsburgh, PA, United States of America

Bernardo Pires