Accenture Global Services Gmbh

Alastair Ross Partington

Cyrille Bataller

Alessio Cavallini

Per Anders Matteus Astrom

Gaëlle Le Roux

Thomas Jean Georges M Moretti

Anders Aström

David Mark Irish

Jarkko Ylipaavalniemi

Jordi Rocamora Marti

Sebastiano Tornesello

James Whitehead

Mark Crego

Virtual access control may include detecting entry of a person into a virtual controlled zone, and counting and/or identifying people including the person entering into the virtual controlled zone. Virtual access control may further include determining an authorization of the person to continue through the virtual controlled zone based on a facial identification of the person, and alerting the person to stop, exit from, or continue through the virtual controlled zone based on the determined authorization. An alarm may be generated if the person violates directions provided by the alert.

Virtual access control

Summarizing, the application relates to a machine-learning system for adaptively changing a matching threshold of a biometric system. The machine-learning system comprises a batch aggregator device operable to receive input data from the biometric system via a communication interface and to aggregate a batch of at least some of the received input data. The machine-learning system further comprises a learning expert device operable to compute a new suggestion for a matching threshold value of the biometric system based on the aggregated batch. Finally, the machine-learning system comprises an output device operable to output the computed new suggestion for the matching threshold of the biometric system via the communication interface.

Machine-learning system for optimising the performance of a biometric system

A system and method for centralized statistical analysis and control of power consumption is provided. The centralized statistical analysis, performed by a centralized power utility management system, may then be compared with one or more goals of the customer. Based on the comparison of the statistical analysis with the one or more goals of the customer, one or more actions may be taken including controlling one or more appliances resident at the customer premises.

Analytics for consumer power consumption

The present disclosure concerns a method of identifying a biometric record of an individual in a database comprising a plurality of biometric records, each record comprising at least one reference biometric sample, the method comprising: receiving, by a biometric identification unit (), an input biometric sample with associated source information; selecting, by the biometric identification unit using a reference table (), and based on said source information a matching process; and applying by said biometric identification unit said selected matching process to at least some of said biometric records of said database to determine whether said input biometric sample matches a reference biometric sample of one of said biometric records.

Biometric matching system using input biometric sample

The present disclosure concerns a method of identifying a biometric record of an individual in a database (), the database comprising at least first and second sets of records, each set comprising at least one record, the method comprising: receiving by a processing device () at least first and second input biometric samples of said individual; performing on the records of said first set a first matching process comprising a first filtering operation followed by a second filtering operation, and performing on the records of said second set a second matching process comprising said second filtering operation followed by said first filtering operation, wherein said first filtering operation comprises comparing said first input biometric sample to a first reference biometric sample of each record, and said second filtering operation comprises comparing said second input biometric sample to a second reference biometric sample of each record; and identifying a biometric record of said individual based on results of the first and second matching processes.

Biometric matching engine

The present disclosure concerns a method of identifying a biometric record of an individual in a database () having a plurality of biometric records, the method involving: during a training phase: applying by a processing device a matching operation to determine scores for a similarity between at least one training biometric sample of each of a plurality of training records and at least one probe sample; based on said scores, determining a threshold value (S,M); and during an identification phase: evaluating at least one reference biometric sample of each of the records of said database to determine a parameter value for each record; selecting a subset of said records by comparing each of said parameter values with said threshold value; and applying a matching operation to the selected records to determine whether an input biometric sample matches a reference biometric sample of one of said selected records.

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Hatfield, United Kingdom

Alastair Ross Partington