US 12,353,532 B2
Passive identification of a device user
Gregory Lee Storm, Parkville, MO (US); and Reza R Derakhshani, Shawnee, KS (US)
Assigned to Jumio Corporation, Sunnyvale, CA (US)
Filed by Jumio Corporation, Sunnyvale, CA (US)
Filed on Apr. 30, 2024, as Appl. No. 18/651,412.
Application 18/651,412 is a continuation of application No. 18/309,661, filed on Apr. 28, 2023, granted, now 11,989,275.
Application 18/309,661 is a continuation of application No. 16/241,508, filed on Jan. 7, 2019, granted, now 11,675,883, issued on Jun. 13, 2023.
Prior Publication US 2024/0281512 A1, Aug. 22, 2024
Int. Cl. G06F 21/00 (2013.01); G06F 21/32 (2013.01); G06V 10/764 (2022.01); G06V 10/82 (2022.01); G06V 40/10 (2022.01); G06V 40/12 (2022.01); G06V 40/16 (2022.01); G06V 40/18 (2022.01); G06V 40/20 (2022.01); G06V 40/70 (2022.01)
CPC G06F 21/32 (2013.01) [G06V 10/764 (2022.01); G06V 10/82 (2022.01); G06V 40/103 (2022.01); G06V 40/12 (2022.01); G06V 40/171 (2022.01); G06V 40/172 (2022.01); G06V 40/18 (2022.01); G06V 40/20 (2022.01); G06V 40/25 (2022.01); G06V 40/70 (2022.01)] 20 Claims
OG exemplary drawing
 
1. A computer-implemented multi-modal biometric authentication method for authenticating a user at a device, the computer-implemented multi-modal biometric method executed by one or more processors and comprising the steps of:
identifying a target user in a vicinity of the device;
detecting, a wireless signal, by equipment capable of proximity sensing the wireless signal;
designating a plurality of distinct biometric vector traits for identifying the target user;
sensing at least a subset of the plurality of distinct biometric vector traits usable to identify the target user, including one or more print types, a retinal scan, a pressure signature, a face scan, one or more gait measures, one or more olfactory biometrics, and one or more auditory biometrics for the target user;
capturing and collecting at least a plurality of different data sets for at least the subset of the plurality of distinct biometric vector traits;
comparing the plurality of different data sets for at least the subset of the plurality of distinct biometric vector traits captured and collected for the target user with at least one of a reference baseline and stored template data in a database;
fusing the plurality of different data sets for at least the subset to generate a multimodal-biometric score, and using the multimodal-biometric score to detect anti-spoofing;
updating reference data sets for the target user in the database; and
detecting the wireless signal and processing the wireless signal to identify a unique effect of the target user on the wireless signal to generate a biometric vector trait for the target user, the biometric vector trait based on the unique effect of the target user and including at least the one or more gait measures of the target user as the target user is in proximity of the device, wherein the unique effect of the target user creates an apparition in the wireless signal, by which each target user has a unique apparition effect and is identified by the unique apparition effect.