The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.
The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.
Patent No.:
Date of Patent:
Oct. 01, 2013
Filed:
Mar. 16, 2010
Vinay Damodar Shet, Princeton, NJ (US);
Maneesh Kumar Singh, Lawrenceville, NJ (US);
Claus Bahlmann, Princeton, NJ (US);
Visvanathan Ramesh, Plainsboro, NJ (US);
Stephen P. Masticola, Kingston, NJ (US);
Jan Neumann, Arlington, VA (US);
Toufiq Parag, Piscataway, NJ (US);
Michael A. Gall, Belle Mead, NJ (US);
Roberto Antonio Suarez, Jackson, NJ (US);
Vinay Damodar Shet, Princeton, NJ (US);
Maneesh Kumar Singh, Lawrenceville, NJ (US);
Claus Bahlmann, Princeton, NJ (US);
Visvanathan Ramesh, Plainsboro, NJ (US);
Stephen P. Masticola, Kingston, NJ (US);
Jan Neumann, Arlington, VA (US);
Toufiq Parag, Piscataway, NJ (US);
Michael A. Gall, Belle Mead, NJ (US);
Roberto Antonio Suarez, Jackson, NJ (US);
Siemens Corporation, Iselin, NJ (US);
Abstract
First order predicate logics are provided, extended with a bilattice based uncertainty handling formalism, as a means of formally encoding pattern grammars, to parse a set of image features, and detect the presence of different patterns of interest implemented on a processor. Information from different sources and uncertainties from detections, are integrated within the bilattice framework. Automated logical rule weight learning in the computer vision domain applies a rule weight optimization method which casts the instantiated inference tree as a knowledge-based neural network, to converge upon a set of rule weights that give optimal performance within the bilattice framework. Applications are in (a) detecting the presence of humans under partial occlusions and (b) detecting large complex man made structures in satellite imagery (c) detection of spatio-temporal human and vehicular activities in video and (c) parsing of Graphical User Interfaces.