Abstract: Described is a system for ordering images. The system receives a plurality of images. Image features are extracted from each image. A set of all possible image pairs are generated for all images. A similarity metric with weights is generated between the images in each image pair in the set, with a net similarity metric thereafter generated by combining the similarity metrics. The images are then ordered according to the net similarity metrics to generate a computer-ordered set of images. The computer-ordered set of images is then displayed to the user, which allows the user to re-order the images to generate a user-ordered set of images. The weights are then optimized to minimize the distance between the computer-ordered set of images and the user-ordered set of images. The similarity metrics are then re-weighted, with the images thereafter being re-ordered according to the new metrics.

Abstract: Disclosed is a method and system for generic object detection using block-based feature computation and, more specifically, a method and system for massively parallel computation of object features sets according to an optimized clock-cycle matrix. The method uses an array of correlators to calculate block sums for each section of the image to be analyzed. A greedy heuristic scheduling algorithm is executed to produce an optimized clock cycle matrix such that overlapping features which use the same block sum do not attempt to access the block at the same time, thereby avoiding race memory conditions. The processing system can employ any of a variety of hardwired Very Large Scale Integration (VLSI) chips such as Field Programmable Gate Arrays (FPGAs), Digital Signal Processors (DSPs) and Application Specific Integrated Circuits (ASICs).

Abstract: A self adapting cognitive-neural method and system for image analysis is disclosed. The method comprises detecting a set of potential items of interest in an image using a cognitive algorithm, refining the set of potential items of interest using a neural analysis, and adapting the cognitive algorithm based on information gained from the results of the neural analysis. The method may further comprise fusing the results of the cognitive and neural algorithms with a fusion classifier. The neural analysis can include eye tracked EEG, RSVP, or presentation to an operator for visual inspection.

Abstract: A method and apparatus are presented for performing wavelet transforms, post transform processing and inverse wavelet transforms whereby hardware complexity is reduced and processor performance is enhanced by performing the forward and inverse wavelet transformations and post transform processing in variable precision arithmetic. Optimal decreases in the operational arithmetic precision of different wavelet scale coefficients, multiplication and weighting operations, and other operations, results in reduced computational complexity, increased speed, and in some cases better signal to noise ratios.

Abstract: A planning approach for obstacle avoidance for a robot arm is disclosed. In particular, the invention relates to a planning approach for obstacle avoidance in complex environments for an articulated redundant robot arm which uses a set of via points surrounding an obstacle as an intermediary point between initial and target arm positions. Via points are generated using visual perception, and possible trajectories through the via points and to the target are rehearsed prior to execution of movement. The disclosed planning method solves the “local minima” problem in obstacle avoidance; a situation in which the obstacle avoidance vectors prevent the arm from making progress toward the target.

Abstract: Described is a signal processing system. The system comprises a signal processing module having signal processing parameters and being configured to receive a plurality of signals. The signal processing module uses the signal processing parameters to output a processed signal, as either a fused signal or a plurality of separate signals. A classification module is included to recognize information encoded in the processed signal to classify the information encoded in the process signal, with the classification having a confidence level. An optimization module is configured, in a feedback loop, to utilize the information encoded in the processed signal to adjust the signal processing parameters to optimize the confidence level of the classification, thereby optimizing an output of the signal processing module.

Abstract: Described is a bio-inspired vision system for object recognition. The system comprises an attention module, an object recognition module, and an online labeling module. The attention module is configured to receive an image representing a scene and find and extract an object from the image. The attention module is also configured to generate feature vectors corresponding to color, intensity, and orientation information within the extracted object. The object recognition module is configured to receive the extracted object and the feature vectors and associate a label with the extracted object. Finally, the online labeling module is configured to alert a user if the extracted object is an unknown object so that it can be labeled.

Abstract: The present invention provides a scalable and reliable collaborative multicast routing for multicasting in hybrid, multi-tiered, mobile heterogeneous wireless networks. It establishes a multicast tree, maintains the established route, detects and prevents most link breakage within the multicast tree by a neighboring node or the cooperation of the neighboring node, and enables merging of partitioned multicast trees of the same multicast group by nodes that participate in one of the partitioned multicast trees. The use of local nodes to collaboratively establish, maintain, recover, and merge the hybrid, multi-tiered mobile wireless networks that use heterogeneous set of mobile wireless nodes is the fundamental basis for the collaborative multicast routing scheme of the present invention.

Abstract: The present invention relates to a hierarchical system for multi-objective shape control of variable stiffness structures. The system operates by initializing a hierarchical hybrid Gur-game controller that is affixed to a variable stiffness structure. The hierarchical hybrid Gur-game controller includes a hierarchy of Gur-games being utilized, at each level of the hierarchy, to control at least two angular rotations and at least one stiffness setting of the variable stiffness structure. The Gur-game controller is utilized to optimize variables, including angular rotations and stiffness settings of the variable stiffness structure to morph into a desired shape. Finally, the variable stiffness structure is morphed into the desired shape according to the optimized angular rotation and stiffness settings.

Abstract: Described is a system for anomaly detection to detect an anomalous object in an image, such as a concealed object beneath a person's clothing. The system is configured to generate a subspace model for a normal class using training images. The normal class represents normal objects in a common class. The system receives a novel image having an object in the common class. A set of geometric landmarks are identified in the object in the novel image for use in registering the image. The novel image is registered by warping the image so that the geometric landmarks coincide in the novel image and the training images, resulting in a warped novel image having an object. Thereafter, the system determines if the object in the warped novel image is anomalous by measuring the distance of the warped novel image from the subspace model. Finally, if anomalous, an operator is notified accordingly.

Abstract: The present invention relates to a method for optimizing the design of a shape morphing structure using a genetic algorithm. The method includes defining design parameters of a surface having variable properties into a chromosome. The variable properties of the chromosome are the actual properties of the chromosome. The chromosome has a total of Nmax genes, where each gene corresponds to a variable property element in the surface. Additionally, each gene has n design parameters, wherein the design parameters are incremental changes to the actual properties of the chromosome. A genetic algorithm is employed to optimize the genes until a fitness level for at least one chromosome has been exceeded. When the fitness value for any chromosome in the population is above a predetermined threshold, then the design process is terminated and the final design solution[s] are the design parameters of the chromosome[s] that exceed the predetermined threshold value.

Abstract: An apparatus configured to obtain, process, and relay data to a user in a coherent and useful manner. An active fiducial is equipped with an interface for receiving and transmitting data. The fiducial may transmit its position using a satellite-based position sensing device such as a GPS. Active fiducials may also be equipped with battery power pack regenerated with solar cells. Similarly, the fiducials can be equipped with at least one video camera or other device having a focal plane array and a computer software system, configured to recognize shapes. The fiducials may also be equipped with inductive coils or other means for sensing metal containing compounds. The active fiducials may be equipped with a gas chromatograph. The active fiducials may use a variety of propulsion means including motor driven tracks, motor driven wheels, propellers, or other device or a combination of devices.

Abstract: The present invention relates to a valuation-based learning system. The system is configured to receive a plurality of inputs, each input being input evidence corresponding to a variable in a Dempster-Shafer Reasoning System. The Dempster-Shafer Reasoning System is a network of interconnected nodes, with each node representing a variable that is representative of a characteristic of a problem domain. A discount weight is then optimized for assigning to each of the inputs. A basic probability assignment (bpa) is generated using the Dempster-Shafer Reasoning System, and where the bpa is an output for use in determining a solution of the problem domain. Finally, a solution to the problem domain is determined using the bpa.

Abstract: Described is a distributed network optimization system implementing distributed particle swarm optimization, which allows multiple nodes to cooperate in searching efficiently for a set of parameter values that optimizes overall network performance. The system comprises a multi-dimensional network parameter space with software agents configured to operate as a cooperative swarm to locate an objective function optima. The software agents are individually distributed across multiple nodes in the network, and each node processes a portion of each software agent to obtain information regarding the local performance of the software agent. A global measure of network performance is then computed based on sharing of local performance information between nodes, which each node uses to adjust its parameters accordingly. In this manner, the global utility of the network can be optimized using local processing only. Also described is a method of utilizing the system.

Abstract: Described is a method for retrieving task information using task-based indexes. The method includes an act of acquiring task-based categories and documents. Task-descriptive symbols are then associated with each task-based category. The documents are indexed to create an index having index words and pointers. The index words reflect the information in the documents and the pointers connect particular index words to particular documents or subparts of documents. The task-descriptive symbols are correlated with the index words to create an alignment of words having similar meaning such that index words are matched with similar task-descriptive symbols. The task-based indexes are formed by grouping the alignment of words with the respective task-based category. A user may use the task-based index by inputting task descriptive symbols into the task-based index to retrieve a document having task information pertaining to the task-descriptive symbols.

Abstract: Described is a fault-tolerant electro-mechanical system that is able to saccade to a target by training and using a signal processing technique. The invention enables tracking systems, such as next generational cameras, to be developed for autonomous platforms and surveillance systems where environment conditions are unpredictable. The invention includes at least one sensor configured to relay a signal containing positional information of a stimulus. At least one actuator is configured to manipulate the sensor to enable the sensor to track the stimulus. A processing device is configured to receive positional information from each sensor and each actuator. The processing device sends a positional changing signal to at least one actuator and adjusts at least one positional changing signal according to the information from each sensor and each actuator to enable the actuator to cause the sensor to track the stimulus.

Abstract: A method and system for determining an optimized artificial impedance surface is disclosed. An artificial impedance pattern is calculated on an impedance surface using an optical holographic technique given an assumed surface wave profile and a desired far field radiation pattern. Then, an actual surface wave profile produced on the impedance surface from the artificial impedance pattern, and an actual far field radiation pattern produced by the actual surface wave profile are calculated. An optimized artificial impedance pattern is then calculated by iteratively re-calculating the artificial impedance pattern from the actual surface wave profile and the desired far field radiation pattern. An artificial impedance surface is determined by mapping the optimized artificial impedance pattern onto a representation of a physical surface.

Abstract: The present invention relates to a system, method, and computer program product for immersive navigation in a virtual environment (VE) suitable for allowing a user to change a view orientation in the VE independently of physical orientation of a user input, such as orientation of the user's head.

Abstract: Described is a system for multi-mission scheduling. The system is configured to compile a list of missions, where each mission includes at least one task. Additionally, each mission has a mission value associated with it such that the mission value reflects an ordering priority of the mission. The system also compiles a list of available resources that can be utilized to complete the tasks. The resources have, varying capabilities of completing tasks. Based on the lists, the system allocates and schedules the resources to complete tasks within the missions to maximize a total mission value of completed missions. Thus, the system schedules multiple missions to maximize the value of completed missions given available resources, whereby a mission is scheduled when the totality of its tasks have been allocated a sufficient amount of resources.

Abstract: The present invention provides a method and apparatus for sensing and determining the shapes of deformable materials, shaped by a plurality of actuators, using sparse sensor network topologies. The method comprises placing a plurality of curvature sensors on the surface of a deformable material to measure the local curvatures of the deformable material. The plurality of curvature sensors generate a collection of sensor data correlated to the local curvatures. Actuator parameters are generated from sensor data by assuming linear approximation between sensors data and actuator parameters. The shape of the deformable material is determined from the generated actuator parameters.