Abstract: A system for improved localization of image forgery. The system generates a variational information bottleneck objective function and works with input image patches to implement an encoder-decoder architecture. The encoder-decoder architecture controls an information flow between the input image patches and a representation layer. The system utilizes information bottleneck to learn useful residual noise patterns and ignore semantic content present in each input image patch. The system trains a neural network to learn a representation indicative of a statistical fingerprint of a source camera model from each input image patch while excluding semantic content thereof. The system can determine a splicing manipulation localization by the trained neural network.

Abstract: Computer vision systems and methods for localizing image forgery are provided. The system generates a constrained convolution via a plurality of learned rich filters. The system trains a convolutional neural network with the constrained convolution and a plurality of images of a dataset to learn a low level representation of each image among the plurality of images. The low level representation is indicative of a statistical signature of at least one source camera model of each image. The system can determine a splicing manipulation localization by the trained convolutional neural network.

Abstract: Computer vision systems and methods for localizing image forgery are provided. The system generates a constrained convolution via a plurality of learned rich filters. The system trains a convolutional neural network with the constrained convolution and a plurality of images of a dataset to learn a low level representation of each image among the plurality of images. The low level representation is indicative of a statistical signature of at least one source camera model of each image. The system can determine a splicing manipulation localization by the trained convolutional neural network.

Abstract: The invention includes systems and methods, including computer programs encoded on computer storage media, for classifying inputs as belonging to a known or unknown class as well as for updating the system to improve is performance. In one system, there is a desired feature representation for unknown inputs, e.g., a zero vector, and the system includes transforming input data to produce a feature representation, using that to compute dissimilarity with the desired feature representation for unknown inputs and combining dissimilarity with other transformations of the feature representation to determine if the input is from a specific known class or if it is unknown. In one embodiment, the system transforms the magnitude of the feature representation into a confidence score.

Abstract: The invention allows riders to quickly and effortlessly strap in and out of their bindings with only one hand, with embodiments for top-entry bindings, rear-entry bindings and hybrid-bindings. The invention can be integrated into bindings or delivered as after-market add-on products that re-use and adapt the riders existing binding.

Abstract: Computer vision systems and methods for localizing image forgery are provided. The system generates a constrained convolution via a plurality of learned rich filters. The system trains a convolutional neural network with the constrained convolution and a plurality of images of a dataset to learn a low level representation of each image among the plurality of images. The low level representation is indicative of a statistical signature of at least one source camera model of each image. The system can determine a splicing manipulation localization by the trained convolutional neural network.

Abstract: A system for improved localization of image forgery. The system generates a variational information bottleneck objective function and works with input image patches to implement an encoder-decoder architecture. The encoder-decoder architecture controls an information flow between the input image patches and a representation layer. The system utilizes information bottleneck to learn useful residual noise patterns and ignore semantic content present in each input image patch. The system trains a neural network to learn a representation indicative of a statistical fingerprint of a source camera model from each input image patch while excluding semantic content thereof. The system can determine a splicing manipulation localization by the trained neural network.

Abstract: The invention includes systems and methods, including computer programs encoded on computer storage media, for classifying inputs as belonging to a known or unknown class as well as for updating the system to improve is performance. In one system, there is a desired feature representation for unknown inputs, e.g., a zero vector, and the system includes transforming input data to produce a feature representation, using that to compute dissimilarity with the desired feature representation for unknown inputs and combining dissimilarity with other transformations of the feature representation to determine if the input is from a specific known class or if it is unknown. In one embodiment, the system transforms the magnitude of the feature representation into a confidence score.

Abstract: The invention allows riders to quickly and effortlessly strap in and out of their bindings with only one hand, with embodiments for top-entry bindings, rear-entry bindings and hybrid-bindings. The invention can be integrated into bindings or delivered as after-market add-on products that re-use and adapt the riders existing binding.

Abstract: A fingerprint characterizing system and method include receiving a fingerprint image at a fingerprint module; extracting a plurality of minutiae points from the fingerprint image, via a fingerprint image sensor; generating a minutiae file of biometric data according to a corresponding location of the plurality of minutiae points on the fingerprint image; generating a pair table from the minutiae file; dividing the pair table into a plurality of subsets; encrypting, via processing circuitry each of the plurality of subsets; comparing, via the processing circuitry each of the encrypted plurality of subsets against one or more existing encrypted subsets stored across a plurality of data clouds; and generating, via the processing circuitry a match table for each of the encrypted plurality of subsets and a corresponding compatible existing encrypted subset stored in the plurality of data clouds.

Abstract: A fingerprint characterizing system and method include receiving a fingerprint image at a fingerprint module; extracting a plurality of minutiae points from the fingerprint image, via a fingerprint image sensor; generating a minutiae file of biometric data according to a corresponding location of the plurality of minutiae points on the fingerprint image; generating a pair table from the minutiae file; dividing the pair table into a plurality of subsets; encrypting, via processing circuitry each of the plurality of subsets; comparing, via the processing circuitry each of the encrypted plurality of subsets against one or more existing encrypted subsets stored across a plurality of data clouds; and generating, via the processing circuitry a match table for each of the encrypted plurality of subsets and a corresponding compatible existing encrypted subset stored in the plurality of data clouds.

Abstract: A secure and scalable data storage system that includes a server and a plurality of clients. The server maintains an access permission file that includes a file-group name, a plurality of client access blocks, a first and second public key, and a signature that is based on a first private key. The signature ensures that only clients who have a certain level of access can modify the contents of the access blocks. Each client access block includes at least one of a first access key, a second access key and a third access key. The access keys are encapsulated within biometric information of the client. The server grants one of a first level of access based on a successful verification of a signed request with the first public key and a second level of access based on a successful verification of the signed request with the second public key.

Abstract: A secure and scalable data storage system that includes a server and a plurality of clients. The server maintains an access permission file that includes a file-group name, a plurality of client access blocks, a first and second public key, and a signature that is based on a first private key. The signature ensures that only clients who have a certain level of access can modify the contents of the access blocks. Each client access block includes at least one of a first access key, a second access key and a third access key. The access keys are encapsulated within biometric information of the client. The server grants one of a first level of access based on a successful verification of a signed request with the first public key and a second level of access based on a successful verification of the signed request with the second public key.

Abstract: Ethanol is non-invasively tested using temperature-modulated spectroscopy (TMS). The TMS approach uses the active control of temperature to vary the spectral response of the IR-LED output, effectively sliding a spectral pulse across the ethanol sample, revealing the peaks and valleys of ethanol's spectral response.

Abstract: Techniques, systems and methods are described relating to combining biometric and cryptographic techniques to support securely embedding data within a token and subsequent biometrically-enabled recovery of said data. Various transformation approaches are described that provide a secure means for transforming a stored or live, secure biometric-based identity token, embedding data into such tokens and biometric-based matching to both verify the user's identity and recover the embedded data. Security enhancements to a range of existing protocols are described using the techniques. Systems using novel protocols based on these techniques are described.

Abstract: A system (100) for the adaptive imaging of a scene includes a digital light processing apparatus (150) adapted for controllably reflecting an image of the scene in at least a first direction to thereby reflect an intensity modulated image of the scene along at least the first direction, an image detector (140) for detecting the intensity modulated image of the scene and generating corresponding image data, and an image data processor (154) for processing the image data into control data and providing the control data to the digital light processing (150) apparatus for control thereof.

Abstract: A user of a mobile device can be authenticated based on multiple factors including biometric data of the user. During an enrollment process of the user, an encryption key is sent to the mobile device via a message. The encryption key is recovered from the message and used to encrypt communications between the mobile device and a server. Biometric data is collected from the user and sent to the server for computing a biometric model (e.g., a voice model, etc.) of the user for later use in authentication. An encrypted biometric model is stored only in the mobile device and the encrypted biometric model is sent to the server for authentication of the user. For authentication, various information including an identification of the mobile device, responses to challenge questions, biometric data including the biometric model, etc. are used at the server.

Abstract: A system and method for measuring impairment in an operator and stopping an impaired operator from operating a vehicle. The method empirically measures an operator's cognitive and motor skills requisite for safely operating a motorized vehicle and verifies the person's identity. The invention includes three interlocking major subsystems. The first subsystem provides generalized impairment measurement unit. The second subsystem interfaces with the impairment measurement unit and a vehicle ignition system and ensures the vehicle does not start if the operator is impaired. The third system determines whether the person blowing into a drug and alcohol analyzer connected to the first system is that person by detecting a various biometric. If the operator is not impaired and their identity is verified the vehicle ignition is enabled. If the operator is indeed impaired beyond a level requisite to safely operate the vehicle the ignition is disabled.

Abstract: The present invention provides a technique for automated selection of a parameterized operator sequence to achieve a pattern classification task. A collection of labeled data patterns is input and statistical descriptions of the inputted labeled data patterns are then derived. Classifier performance for each of a plurality of candidate operator/parameter sequences is determined. The optimal classifier performance among the candidate classifier performances is then identified. Performance metric information, including, for example, the selected operator sequence/parameter combination, will be outputted. The operator sequences selected can be chosen from a default set of operators, or may be a user-defined set. The operator sequences may include any morphological operators, such as, erosion, dilation, closing, opening, close-open, and open-close.

Abstract: A system (100) for the adaptive imaging of a scene includes a digital light processing apparatus (150) adapted for controllably reflecting an image of the scene in at least a first direction to thereby reflect an intensity modulated image of the scene along at least the first direction, an image detector (140) for detecting the intensity modulated image of the scene and generating corresponding image data, and an image data processor (154) for processing the image data into control data and providing the control data to the digital light processing (150) apparatus for control thereof.