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Object detection approach using generative sparse, hierarchical networks with top-down and lateral connections for combining texture/color detection and shape/contour detection

United States Patent

9,092,692
July 28, 2015
View the Complete Patent at the US Patent & Trademark Office
Los Alamos National Laboratory - Visit the Technology Transfer Division Website
An approach to detecting objects in an image dataset may combine texture/color detection, shape/contour detection, and/or motion detection using sparse, generative, hierarchical models with lateral and top-down connections. A first independent representation of objects in an image dataset may be produced using a color/texture detection algorithm. A second independent representation of objects in the image dataset may be produced using a shape/contour detection algorithm. A third independent representation of objects in the image dataset may be produced using a motion detection algorithm. The first, second, and third independent representations may then be combined into a single coherent output using a combinatorial algorithm.
Paiton; Dylan M. (Rio Rancho, NM), Kenyon; Garrett T. (Santa Fe, NM), Brumby; Steven P. (Santa Fe, NM), Schultz; Peter F. (Los Alamos, NM), George; John S. (White Rock, NM)
Los Alamos National Security, LLC (Los Alamos, NM)
14/ 026,812
20140072213
September 13, 2013
STATEMENT OF FEDERAL RIGHTS The United States government has rights in this invention pursuant to Contract No. DE-AC52-06NA25396 between the United States Department of Energy and Los Alamos National Security, LLC for the operation of Los Alamos National Laboratory.