Abstract: Face recognition systems are vulnerable to the presentation of spoofed faces, which may be presented to face recognition systems, for example, by an unauthorized user seeking to gain access to a protected resource. A face liveness detection method that addresses this vulnerability utilizes motion analysis to compare the relative movement among three regions of interest in a facial image and based upon that comparison to make a face liveness determination.

Abstract: Methods and systems are provided for an AdHoc enrollment process. A user may be able to enroll and be verified by a system for a variety of actions or authentications without being forced to turn over personally identifiable information and without having to formally enroll. The system may compare captured biometric information with existing biometric information and may identify the user without the use of personally identifiable information.

Abstract: A system for identifying one or more product engagements includes one or more microsensors configured to measure one or more signals indicative of one or more near-product engagements within a retail environment. Near-product engagements product movement, customer proximity to products, temperature, and the like. In some embodiments, the system may be configured to generate spatial relationship data associated with one or more spatial relationships between one or more transmitting electronic devices and one or more sensor units. The system may perform one or more filtering steps on the near-product engagement or spatial relationship data and providing the filtered data to a user interface.

Abstract: Entity resolution (i.e., record linkage) involves the analysis/discovering of datasets that refer to the same real world entity. Analysis typically involves transformation and comparison of different fields of the dataset followed by the application of often domain/data specific logic for determining datasets that refer to the same real world entity (e.g., person). Consider, a bulk mailing of product catalogs to potential customers. Some individuals may have numerous public records that identify the individual differently. Illustratively, several records associated with Jane Doe at her current home address may exist: one record with her name listed as J. Doe, a second record as Jane H. Doe, a third record as Doe, Jane, and a fourth record as Jan Doe (a misspelling). Conceivably, the bulk mailing could unwittingly send multiple catalogs to Jane Doe at her current address, one for each name variation. The entity resolution process described herein can overcome such problems.

Abstract: Methods and systems are provided for an AdHoc enrollment process. A user may be able to enroll and be verified by a system for a variety of actions or authentications without being forced to turn over personally identifiable information and without having to formally enroll. The system may compare captured biometric information with existing biometric information and may identify the user without the use of personally identifiable information.

Abstract: A system and method of analyzing data receives a user-specified selection of a data source, a user-specified selection of a type of data representation, and a user-specified description of a view to be constructed in accordance with the user-specified selection of the type of data representation. An application program interface (API) function generates a multidimensional query based on the user-specified type of data representation and the user-specified description of the view to be constructed, and submits the multidimensional query to the an On-line Analytical Processing (OLAP) server. The application program interface (API) function receives a multidimensional response from the OLAP server containing results acquired by the multidimensional query of the data source, and generates the view based on the results contained in the multidimensional response and in accordance with the user-specified selection of the type of data representation and the user-specified description of the view.

Abstract: In real biometric systems, false match rates and false non-match rates of 0% do not exist. There is always some probability that a purported match is false, and that a genuine match is not identified. The performance of biometric systems is often expressed in part in terms of their false match rate and false non-match rate, with the equal error rate being when the two are equal. There is a tradeoff between the FMR and FNMR in biometric systems which can be adjusted by changing a matching threshold. This matching threshold can be automatically, dynamically and/or user adjusted so that a biometric system of interest can achieve a desired FMR and FNMR.

Abstract: Methods and systems are provided for an AdHoc enrollment process. A user may be able to enroll and be verified by a system for a variety of actions or authentications without being forced to turn over personally identifiable information and without having to formally enroll. The system may compare captured biometric information with existing biometric information and may identify the user without the use of personally identifiable information.

Abstract: Methods and systems for of generating reporting data in an automated, efficient, and risk-free fashion relating to an identification match relating to a probe image are disclosed. Methods include automatically capturing a comparison area in the probe image and a comparison area of a candidate image based on examiner input; facilitating a determination of whether a similarity or a dissimilarity exists between the comparison area in the probe image and the comparison area of the candidate image; automatically recording metadata based on the determination of whether the similarity or the dissimilarity exists between the comparison area in the probe image and the comparison area of the candidate image and updating an audit log; and generating a report comprising the metadata.

Abstract: Methods and systems for of generating reporting data in an automated, efficient, and risk-free fashion relating to an identification match relating to a probe image are disclosed. Methods include automatically capturing a comparison area in the probe image and a comparison area of a candidate image based on examiner input; facilitating a determination of whether a similarity or a dissimilarity exists between the comparison area in the probe image and the comparison area of the candidate image; automatically recording metadata based on the determination of whether the similarity or the dissimilarity exists between the comparison area in the probe image and the comparison area of the candidate image and updating an audit log; and generating a report comprising the metadata.

Abstract: A ridge flow based fingerprint image quality determination can be achieved independent of image resolution, can be processed in real-time and includes segmentation, such as fingertip segmentation, therefore providing image quality assessment for individual fingertips within a four finger flat, dual thumb, or whole hand image. A fingerprint quality module receives from one or more scan devices ridge-flow—containing imagery which can then be assessed for one or more of quality, handedness, historical information analysis and the assignment of bounding boxes.

Abstract: Systems and methods for enhancing confidence in a biometric search result include submitting one or more biometric samples to a biometric search engine. In response to the one or more submitted biometric samples, a plurality of candidates identified as potentially associated with the one or more submitted biometric samples is received from the biometric search engine. Each identified candidate has associated biographic information. The biographic information associated with each identified candidate is submitted to a relationship detection engine. In response to the submitted biographic information, an identified relationship between at least one of the identified candidates and one or more other individuals is received from the relationship detection engine.

Abstract: A blockchain database employs cryptography and other methods to implement and protect a distributed, publicly-amendable ledger. Transactions in a blockchain ledger are intentionally anonymous; however, there are cases where it would be useful to be able to verify or disprove a claim of identity of a contributor of a blockchain transaction. Biometrics can be used to link a human being to digital information using their unique physical traits in a way that is analogous to a handwritten or digital signature. An exemplary embodiment disclosed herein describes methods to create and store data in a blockchain transaction such that it can be used in the future to biometrically verify the identity of the contributor of the transaction, and use encoded biometric data to determine whether the blockchain transaction was created or not created by a particular individual.

Abstract: Spoofed faces are unlikely to reflect a liveness detection image in the same manner as live faces. To determine liveness of a subject face, a liveness detection image is displayed on a screen of a face recognition device in the direction of the subject face, and a reflection image of the subject face is captured while the liveness detection image is displayed. The reflection image is analyzed to determine whether the reflection image contains any reflections of the liveness detection image, and a liveness determination is made based on the location and/or character of any such reflections.

Abstract: Systems and methods acquire and/or generate multiple different images of the same biometric identity, identify specific instances of biometric features in each of the different images, and merge the identified specific instances of biometric features into a data record that provides a digital representation of the biometric identity. Examples of biometric identities include fingerprints, handprints, palm prints, and thumbprints. In one embodiment, a counter is associated with each specific instance of a biometric feature found in the multiple images. Specific instances of biometric features found most frequently have high counts and are indicative of true identifications; those with low counts are indicative of false identifications. A threshold distinguishes between true and false identifications. Those specific instances with counts below the threshold are excluded when the digital representation of the biometric identity is generated.

Abstract: A decentralized biometric identity authentication method utilizes biometrics captured on a mobile device to perform identity authentication against data that was registered as part of an identity proofing process and is thus trusted. The user registers his or her biometric using the user's mobile device and associates it with the user's electronic identity as part of a supervised identity proofing process, thus forming a proofed identity, and registers the proofed identity with a federated identity system. To later access the resources of the federated identity system, the user logs in with his or her biometrics. The methods described herein are useful, for example, in the travel, healthcare, and financial services fields.

Abstract: Methods and systems for high-speed filtering of candidate fingerprint images in a gallery using a non-reference-point based matching involving histograms of tokens representing minutia data. The method or system may involve detecting minutia patterns in a probe image, defining tokens that represent the minutia patterns detected in the probe image, measuring a degree of similarity between the probe image and each gallery image by comparing a probability of occurrence of a set of the tokens defined for the probe image with a probability of occurrence of the same set of tokens in that gallery image, and identifying as a candidate for a match to the probe image each gallery image for which the measured degree of similarity satisfies a criterion.

Abstract: Methods and computer systems execute biometric operations in parallel. The performance of a biometric operation includes receiving a job request to perform the biometric operation. The job request includes input data, identifies a database to be used in the performance of the biometric operation, and specifies a function to be performed. The biometric operation is restructured as one or more tasks. A number of entries in the database is assigned to each of the one or more tasks. An independent worker process is generated for each different core of the multi-core processor. Each task of the one or more tasks is assigned to one of the worker processes. Results produced by each worker process assigned one of the one or more tasks are collected. A result of the biometric operation based on the collected results is reported.

Abstract: Systems and methods for repairing cross-linked biometric records receive a set of biometric records. Each biometric record contains at least one biometric sample in a non-textual modality. One or more of the biometric records in the set of biometric records is potentially a cross-linked biometric record having at least two biometric samples that are associated with different individuals. Crosslink resolution is performed on the set of biometric records by searching for a match between a biometric sample in a given non-textual modality of a given biometric record with each biometric sample of the same given non-textual modality in each of the other biometric records in the set of biometric records. During the crosslink resolution, biometric sample may be removed from one biometric record and merged with another biometric record.

Abstract: Entity resolution (i.e., record linkage) involves the analysis/discovering of datasets that refer to the same real world entity. Analysis typically involves transformation and comparison of different fields of the dataset followed by the application of often domain/data specific logic for determining datasets that refer to the same real world entity (e.g., person). Consider, a bulk mailing of product catalogs to potential customers. Some individuals may have numerous public records that identify the individual differently. Illustratively, several records associated with Jane Doe at her current home address may exist: one record with her name listed as J. Doe, a second record as Jane H. Doe, a third record as Doe, Jane, and a fourth record as Jan Doe (a misspelling). Conceivably, the bulk mailing could unwittingly send multiple catalogs to Jane Doe at her current address, one for each name variation. The entity resolution process described herein can overcome such problems.