NIST Facial Recognition Mask Accuracy Nov 2020 Results Analyzed
In July, NIST found that face masks negatively impacted face recognition created before coronavirus significantly. Now, NIST released a report on recent algorithms developed after Mid-March for testing on face masked subjects.
Do these new algorithms perform better with face masks? IPVM investigates.
Executive *******
**** ***** ******** ** ************* ****** the ******** ** **** *********** ********** despite ************* ****** **** ** ****** algorithms *** ****** ********. ***** *** an *********** *******, *** *** *** best-performing ********** **** ********* ***-******** *** several *** ********** *** ***** ***** close ** ***%. **** ***** *** a *********** ********* *** **** *********** algorithms *** ***-***** ****** ** ***** that *** ******** ** ***** ******* may ** ******* ******** ** ****.
Real-World ************
***-*****, ********** ***** ***** ************ ******* or ***** ***-**-**** ***********, *** ***-**-*** verification, **** ** ********** ** ***** face *********** ********* *** ****** **** widespread **** **** ***. **** **** was ******* **** **** *** *****, because ******* **** ***, ***** ******** at *****, *** ******** ********** **** shots, *** ******** *** ***** ******* impacted **** **** ********** ******* ** even ********* ****** ***** ** *****.
** ********, *** ********** ********* **** no *********** ** ********** ***** ** time *** *** *** *********** ********** algorithms ** ****-***** ********* *** ******* even ***** ** ****** ********. ***-*****, especially **** ***** **** *********** *** tasks ***** **** ****** *******, ****** be ****.
New ***** ********
************************** ******** *** ****** ** ******* face ***** ** ********. **** ****~* ******* ****** ******** ****** ***** with ******* ** ******* **** ~* million **** *********** ****** *** ************/ 1:1 ******** (*.*. ** *** ****** crossing ***** ******* *** **** *****). The **** *********** ****** **** ****-******* and ***** ** *********** ******* **** a ***** **********. **** *** ******* as ***/*** ***** *.*. **** *** are *** * *** ******. *** border ******** ****** *** *** ****** with *** ***/*** *****-* ****-******* ***** standards *** ** **** ***** **** distorted. ***** ****** **** ***** ** trained ********* ** *********** ********** ******* harsh ******, ***** ***** **** *********** much ****** **** ************ ***-***** *** more ******* ** ****** ******* ******* WDR ******.
**** ***** ******* “*****” ** *** border ******** ******. **** ****** * colors ** *** ***** ***** (*****-**** and *****) *** ***** * **** in *** ****** (*** *** *****), 2 ********** (**** *** *****), *** 3 ****** ** **** ******** (***/**** unobstructed, ******/**** ********* *******, ****/**** ****** up ** ***-*****, ********** ******** ****).
**** ****** ** *** ***-**-*** ************ accuracy ** ***** **********/**** ***** **** **** *** ***** match **** *** ** */**,***. **** is **** ******* **** ***-**-**** (*.*., video ************) ***** ** ** ************* harder *******.
Not **** *** *******
**** *** ********** *** ****** **** but ********** *** ***** ******** ** masks, ** ****** ******* *******, *** the **** ********* *** ** *** first *****. * ** *** ** new ********** *** ********** ** **+% with *** ******-****-****-**** ***** ******** ** only * ** *** ******** ** algorithms, *******, ***** * *** ***** the *** **********.**** ***** ********* ********** **** **** greatly ********, **** ******* *&* **** went **** **% ** **% ********, but ***** *** ********** ********* ****** (up ** ***% ***** *****) ***, in *** **** ** ********* *+*, their *** ********* ********* ******** ****** than ***** *** ***.
********
**** ***** ******** ******** ** ******* degrees, **** ****** ***** ****** **** impact, *** ** **** *****, ****** masks ****** * ****** ******.******** ******* ** *** *****, *** the ****** ** ****** ********. *** new **** *** ********* ********* ******* from **.*% ** **.*% **** * mask, ******* **** **.*% ** **.*%, and *** ********* ********* **** *** first ***** **** ******* **** **.*% to **.*%.
**** **** **** *********** ** ****** subjects ** ******* ** ******** ** 2017 **** *********** ******* *****:
*** ******* *********** ** **** *********** with **** ***** ** ********** ** the *****-**-***-*** ** ******** ****** ** mid-2017
*** ******* ****** *** **** ********, which ** **** *****, *********** ** over **** *** *** ******** ** true ************ ********. ***** ***** *** a ****** ****** **** ***** **** (N95 *****). ****, ***** *******, **** darker ***** (***** *** ***) ****** a ******** ****** ****** **** ******* (white *** ****) *******, **** *** not **********.
Changing ********** *** *****
******** ********** *** **** ***** *** effect ** ****-***** ** ********** *** true ************ **** **** **** ******* effects ** ***** ***********, ** ***** in *** ******* *****.
Exposing *****
** ** ** ****, ** *** make ***** *** ***** ** ***** their ***** ******** ***** ****, ** this *** ******* ******** *** **** verification ****.
*******
*** *** ********** *** *** *********** designed *** ***, *** *** **** processing ** ******* **********, *** ***** be ******** ** *** *********, ** the **** ** * *** **** algorithm ******* **** ***** ***** **** a *********** ********* ** ********* ********** that **** *** **** ****** ****** by *** **** ** *** ***** despite ** ********* ** ** **.
** ******, **** ******** ****'* ***** to **** ******** ** ******** **** are ***** ** ** **** *** such *****.
**** ** *** *****. **'* * lot ****** ** ** **** ** a ********* ********* ** * *** days ** ******* **** **** * long-continuous ********** **** **** ***** **** faces.
*'* ******* ***** *** ***** ******** size **** ** ********** ** **** readers.
* ** ***. ***************** ** * ***** ***** ** ask ********* ** *** ***** **** membership.
* **** **** **** ********* ** update ***** **** *******, ** *** same *** **** ** ** ******** other **** **** *******.
** ***** **** **** ************ ** **** ***** ********* **********. And ** **** ******** ** ****** our ******** ** *** *******.
******* ** **** ***** *** * database **** ********, ****** ***** ** Shutterfly *** ** ****** ****** *** whole ******** *** ***** *******.
* **** * **** ****** ****** their ***** ********** *****, *** *** free.
**** *** ****** ** **** ****** labeled *** ********* **** ******** ** the ***** ********** *** ***** ********** organizations. **** ***'* **** **** ** do"**-**** **********", ******* *****, *********, *** *******-******** all **** ** ** *******.
*** **** ** **** ************ ***** footage: ***** **** ***** **** ******, possibly ** * ********, **** ******* lighting **********, ***. *** *** ******** is *** **** *** ***** ******* performance ***** **** ***** **** * large ******** *****.
********* **** ******* ** ********* ********, but (** **** *****) ***** ***...*****. I ******************** **** ********/********* *** ****** ** perform ***** ***** ***** *** ****, rather **** * ***** *****'* (****'*) data. ** ******, **** ******** ****'* going ** **** ******** ** ******** that *** ***** ** ** **** for **** *****.
*'* ******* ***** *** ***** ******** size **** ** ********** ** **** readers. *** **** *******' ******** ***** in *** ********? *********? ********? **** could *********** ****** *** ********* ******** that *** ***.
* **** **** **** ********* ** update ***** **** *******, ** *** same *** **** ** ** ******** other **** **** *******. ******* ** the ****** **** *** *********** **** other ************ **** *** **** *****, such ** ******** ********** *****.