Abstract: A system authenticates sound verbalized or otherwise generated by a live source within a monitored setting for voice-controlled or sound-controlled automation of a responsive process. One or more classifiers each generate a decision value according to values of predetermined signal features extracted from a captured digital stream, and a sound type classification is computed according to an aggregate score of a predetermined number of decision values. The actuation of the responsive process is authenticated when the system discriminately indicates the captured sound signals to be verbalized or generated by a live source. The responsive process is thereby suppressed when the sound is instead determined to be reproduced or otherwise previously transduced, for example by a transmission or recording.

Abstract: Captured samples of a physical structure or other scene are mapped to a predetermined multi-dimensional coordinate space, and spatially-adjacent samples are organized into array cells representing subspaces thereof. Each cell is classified according to predetermined target-identifying criteria for the samples of the cell. A cluster of spatially-contiguous cells of common classification, peripherally bounded by cells of different classification, is constructed, and a boundary demarcation is defined from the peripheral contour of the cluster. The boundary demarcation is overlaid upon a visual display of the physical scene, thereby visually demarcating the boundaries of a detected target of interest.

Abstract: A system and method are provided for taxonomically distinguishing grouped segments of signal data captured in unconstrained manner for a plurality of sources. The system comprises a vector unit constructing for each of the grouped signal data segments at least one vector of predetermined form. A sparse decomposition unit selectively executes in at least a training system mode a simultaneous sparse approximation upon a joint corpus of vectors for a plurality of signal segments of distinct sources. The sparse decomposition unit adaptively generates at least one sparse decomposition for each vector with respect to a representative set of decomposition atoms. A discriminant reduction unit executes during the training system mode to derive an optimal combination of atoms from the representative set. A classification unit executes in a classification system mode to discover for an input signal segment a degree of correlation relative to each of the distinct sources.

Abstract: A system and method are provided for distinguishing biota, such as insect types, from overall images, images of their wings or of other body parts. The system and method exploit various techniques described herein, in combination with large scale capture of sample imagery to achieve a flexible mechanism for automated classification on biota of any type.

Abstract: A system is provided for adaptively conformed imaging of work pieces having disparate configurations, which comprises a mount unit for holding at least one work piece, and an imaging unit for capturing images of the work piece held by the mount unit. At least one manipulator unit is coupled to selectively manipulate at least one of the mount and imaging units for relative displacement therebetween. A controller coupled to automatically actuate the manipulator and imaging units executes scene segmentation about the held work piece, which spatially defines at least one zone of operation in peripherally conformed manner about the work piece. The controller also executes an acquisition path mapping for the work piece, wherein a sequence of spatially offset acquisition points are mapped within the zone of operation, with each acquisition point defining a vantage point for the imaging unit to capture an image of the work piece from.

Abstract: A system and method are provided for distinguishing between a plurality of remote sites accessed through a network interconnection by a reference site based upon envelope characteristics of communication signals transmitted therebetween. Communications signals transmitted during an interconnected session established between one of the remote sites and the reference site are time-captured in a plurality of data segments. The time-captured segments are parsed to selectively generate for each the interconnected remote sites an envelope signal indicative of at least one resource allocation response thereof during the interconnection session, the envelope signal being defined by values of at least a first predetermined envelope parameter acquired from the time-captured segments. Based on the envelope signal, a characteristic signature is established for each interconnected remote site to be identified.

Abstract: A system and method are provided for distinguishing biota, such as insect types, from overall images, images of their wings or of other body parts. The system and method exploit various techniques described herein, in combination with large scale capture of sample imagery to achieve a flexible mechanism for automated classification on biota of any type.

Abstract: A system and method are provided for discriminating the nature of traffic flowing through a computer network. Various types of traffic are distinguished. For example, traffic sourced by a software application that generates them may be distinguished. The problem of detecting malicious traffic either originating outside a target network, or inside a target network from a compromised computer is addressed, as is the problem of distinguishing malicious traffic from legitimate web surfing or other applications activity. Traffic distinctions are made based on signal envelope characteristics in such manner as to preserve robust performance even when the subject traffic is encrypted.

Abstract: A system and method are provided for taxonomically distinguishing grouped segments of signal data captured in unconstrained manner for a plurality of sources. The system comprises a vector unit constructing for each of the grouped signal data segments at least one vector of predetermined form. A sparse decomposition unit selectively executes in at least a training system mode a simultaneous sparse approximation upon a joint corpus of vectors for a plurality of signal segments of distinct sources. The sparse decomposition unit adaptively generates at least one sparse decomposition for each vector with respect to a representative set of decomposition atoms. A discriminant reduction unit executes during the training system mode to derive an optimal combination of atoms from the representative set. A classification unit executes in a classification system mode to discover for an input signal segment a degree of correlation relative to each of the distinct sources.

Abstract: A system and method are provided for distinguishing between a plurality of sources based upon unconstrained acoustic signals captured therefrom. A spectrographic transformation is applied to time-captured segments of acoustic signals to generate a spectral vector for each. A selectively executed sparse decomposition includes in a training system mode simultaneous sparse approximation upon a joint corpus of spectral vectors for a plurality of acoustic signal segments from distinct sources. At least one sparse decomposition is executed for each spectral vector in terms of a representative set of decomposition atoms. Discriminant reduction executes during the training system mode to down-select from the representative set an optimal combination of atoms for cooperatively distinguishing acoustic signals emitted by different distinct sources.