Siemens Corporation

Toufiq Parag

Visvanathan Ramesh

Maneesh Kumar Singh

Jan Neumann

Stephen Price Masticola

Vinay Damodar Shet

Claus Bahlmann

Michael A Gall

Roberto Antonio Suarez

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.

Predicate logic based image grammars for complex visual pattern recognition

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Piscataway, NJ, United States of America

Toufiq Parag