A method for configuring a pattern recognition system, the method comprising: receiving object recognition data from at least one first local image processing system, wherein the object recognition data includes at least one of images, compressed representations of images, transformed representations of images, sensor data, salient features, classification objects, output from a behavior modeling engine and output from a rules inference engine; storing the object recognition data in at least one global pattern recognition database of a centralized expert pattern recognition system, the global pattern recognition database being constructed from information received from a plurality of local image processing systems; determining, by a processor of the centralized expert pattern recognition system, configuration data for updating a local classification knowledgebase or a local behavioral knowledgebase or a local rules inference knowledgebase or pattern recognition routines or for updating algorithms for feature extraction, classification, behavior modeling and rules inference, for a second local image processing system, the configuration data using at least in part the object recognition data received from the at least one first local image processing system; and transmitting the configuration data to the second local image processing system; wherein the configuration data includes updates to a local classification knowledgebase or a local behavioral knowledgebase or a local rules inference knowledgebase or pattern recognition routines or updates to algorithms for feature extraction, classification, behavior modeling and rules inference; updating the second local imaging processing system using the transmitted configuration data; wherein the updates to the local classification knowledgebase or the local behavioral knowledgebase or the local rules inference knowledgebase or the pattern recognition routines or the updates to the algorithms for feature extraction, classification, behavior modeling and rules inference modify and improve the performance of the second local image processing system; further comprising receiving, by the centralized expert pattern recognition system, the direct output of a local image processing system's feature extraction engine classification engine, behavior modeling engine and/or rules inference engine and use the data received from individual local image processing systems to modify and improve the performance of a group of local image processing systems having at least one common system parameter; characterized in that the data received from the individual local image processing systems is also used to evaluate and verify the effectiveness of the local image processing algorithms and to determine if changes to these algorithms are needed. receiving object recognition data from at least one first local image processing system, wherein the object recognition data includes at least one of images, compressed representations of images, transformed representations of images, sensor data, salient features, classification objects, output from a behavior modeling engine and output from a rules inference engine; storing the object recognition data in at least one global pattern recognition database of a centralized expert pattern recognition system, the global pattern recognition database being constructed from information received from a plurality of local image processing systems; determining, by a processor of the centralized expert pattern recognition system, configuration data for updating a local classification knowledgebase or a local behavioral knowledgebase or a local rules inference knowledgebase or pattern recognition routines or for updating algorithms for feature extraction, classification, behavior modeling and rules inference, for a second local image processing system, the configuration data using at least in part the object recognition data received from the at least one first local image processing system; and transmitting the configuration data to the second local image processing system; wherein the configuration data includes updates to a local classification knowledgebase or a local behavioral knowledgebase or a local rules inference knowledgebase or pattern recognition routines or updates to algorithms for feature extraction, classification, behavior modeling and rules inference; updating the second local imaging processing system using the transmitted configuration data; wherein the updates to the local classification knowledgebase or the local behavioral knowledgebase or the local rules inference knowledgebase or the pattern recognition routines or the updates to the algorithms for feature extraction, classification, behavior modeling and rules inference modify and improve the performance of the second local image processing system; further comprising receiving, by the centralized expert pattern recognition system, the direct output of a local image processing system's feature extraction engine classification engine, behavior modeling engine and/or rules inference engine and use the data received from individual local image processing systems to modify and improve the performance of a group of local image processing systems having at least one common system parameter; characterized in that the data received from the individual local image processing systems is also used to evaluate and verify the effectiveness of the local image processing algorithms and to determine if changes to these algorithms are needed.