Part 2: System Performance Evaluation

Laboratory staff will systematically attempt to spoof the system and also collect corresponding live data

• 1000 live attempts
• 1000 attempts for different presentation attacks

The parameters adopted for the performance evaluation will be the following:

Evaluation per system

• Attack presentation classification error rate (APCER): proportion of attack presentations using the same PAI species incorrectly classified as bona fide presentations at the PAD subsystem in a specific scenario


• Bona fide presentation classification error rate (BPCER): proportion of bona fide presentations incorrectly classified as presentation attacks at the PAD subsystem in a specific scenario


• Attack presentation non-response rate (APNRR): proportion of attack presentations using the same PAI species that cause no response at the PAD subsystem or data capture subsystem


• False Reject Rate (FRR) : number of false rejections as a proportion of the total number of biometric claims that ought to have been accepted


• Imposter attack presentation match rate (IAPMR): in a full-system evaluation of a verification system, the proportion of imposter attack presentations using the same PAI species in which the target reference is matched


• Full system processing duration (FS-PD): duration required for the data capture subsystem and comparison subsystem to acquire and process a sample, inclusive of PAD subsystem processing duration

Definitions:

Presentation Attack: presentation to the biometric data capture subsystem with the goal of interfering with the operation of the biometric system

Presentation Attack Instrument (PAI): biometric characteristic or object used in a presentation attack

In the case here PAI species are the known and unknown spoof recipes that will be used in this competition

Rates are based on the assumption of a threshold of 50. Quality and match scores will be computed based on the collected images to support efforts to maintain fairness between the submitted systems.

Declaration of the Winner

• The winner will be awarded based on minimum overall classification error for Liveness Only and Verification with liveness. One winner for each category will be awarded.