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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 Application

*** PATENT GRANTED ***
20150325007
9,477,901
A1
View the Complete Application 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)
14/ 805,540
July 22, 2015
STATEMENT OF FEDERAL RIGHTS [0002] 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.