Abstract: Methods and computer program products are disclosed for the real-time classification of text from a region of interest within an image sample. A feature extractor extracts feature data associated with a plurality of region features from the region of interest. The plurality of region features are selected as to minimize the time necessary for feature extraction. A neural network preclassifier selects one of a plurality of associated source classes for the region of interest according to the extracted feature data. A plurality of classification systems are each associated with one of the plurality of source classes. Each of the plurality of classification systems are operative to classify individual characters within the region of interest when the associated source class of the classification system is selected.

Abstract: A system in accordance with the present invention tasks a team of autonomous unmanned vehicles. The system includes a first team member and a second team member. The first team member has a first level of autonomy. The second team member has a second level of autonomy. The first level of autonomy is different than the first level of autonomy. The first team member is given instructions corresponding to the first level of autonomy. The second team member is given instructions corresponding to the second level of autonomy.

Abstract: A system processes asynchronous requests from members of a team of autonomous unmanned vehicles. The system includes a user request interface for receiving a request from a single team member and a request manager for performing a task in response to the request and returning a result of the task to the user request interface. The user request interface transfers the result to the single team member without communicating to any other members of the team.

Abstract: A method and computer product is disclosed for arbitrating the outputs of a plurality of recognizers to select a hypothesis associated with a given input from a plurality of hypotheses. Fuzzy membership states are assigned to respective candidate outputs of the plurality of recognizers. At least one rule is selected according to the assigned fuzzy membership states. A selected rule provides a determined amount of support mass for an associated one of the plurality of hypotheses and a determined amount of uncertainty mass. A support value for each hypothesis and an overall uncertainty are determined from the provided mass values. A hypothesis having a highest support value while having an acceptable low level of uncertainty is selected.

Abstract: A method and computer program product are disclosed for determining an optimal classifier model for a pattern recognition system and updating the determined model to recognize new output classes. An initial plurality of classifier models are selected from a set of generated classifier models. An optimal representative classifier for each classifier model is selected according to an iterative optimization routine. The representative classifier having the highest associated value for a fitness function is accepted.

Abstract: A method and computer product is disclosed for analyzing video surveillance data from a plurality of video inputs recording entrants to a secured location. A plurality of entrant profiles are constructed, detailing typical attributes of the entrants, via data mining algorithms. Video inputs are analyzed, with a plurality of independent automated decision-making systems each determining if an abnormal condition exists based upon the constructed profiles. The determinations of the plurality of decision-making systems are then processed to determine if an alarm condition exists.