Predicate logic based image grammars for complex visual pattern recognition
US8548231B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Mar 16, 2010 |
| Grant date | Oct 1, 2013 |
| Priority date | — |
| Expiry date | Mar 27, 2032 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V10/765
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
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.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.