Masks Cause Major Facial Recognition Problems

By Rob Kilpatrick, Published on Feb 24, 2020

Coronavirus is spurring an increase in the use of medical masks, which new IPVM test results show cause major problems for facial recognition systems.

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IPVM tested four facial recognition systems to see how they performed with masks:

The 1-minute video below overviews our findings:

Masks *********** ****** *********** ***********

** *** *****, ****** recognition ********** ******* ************ (over ** ****** **********) when ******* ****-***** **** masks, **** ******** *** recognized ** *** ** most *****, *** ** faces **** ******** **** of *** ****.

************'* ********** ********* **** ** ************ recognize ********, *** **** required ********** ** ** decreased **** **** ** medium ** ***. ***** recognition *** ********, ** is ******* **** **** will ****** ** ***** identifications ** ***** *********** with ******** ** ********* of ********.

Further ******** ********

** ** ******** **** these ************* ***** ******* masked **** *********** **** further ******** ** ***** algorithms. *******, *************, ********* will **** **** ***** points ** **** *********** on ** ** **** of *** **** ** covered, ****** *********** *********, even **** ********.

Drastically ******* **********

***** *****, **** ******** to *** **** ******* not ******* * ****, confidence ******* ** **** 60 ****** **** ******* a ******* ****, **** nearly ***% ********** ** just **** **% ** the********* **** **** **** rec ******.

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** ***** ** ********* a **** ** ***** levels, ******* ********** ****** to ** ******* ** ~25%. *******, *********** ******** inconsistent ** **** *******, with **** ******** ********, but *** **********. **** was ********** ****** **** hair ******* *** *******'* forehead, ****** ** **** difficult ** ****** *** face.

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**************** *********, **** *********** reduced ********** *** ******** total ******, **** **** using *** ********** ***** requirements. *** *******, *** face ***** ******* **** only **-** **********, ******* of **-** **** *** same ******* *** *** wearing * ****.

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Avigilon **** *********** **** ******** *** **** ******/*** **********

** *** *****,********'* ****** ************** *** **** *********** rates, *********** *** ******** walking ******* *** ***** when ***** ****** ** low ********** ******** (******** does *** **** ***** confidence ******).

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*******, **** **** ***** recognition ****** ** *** tests ***** * ***** population, ***** ****** *** assume ** ***** ******** similarly ** ****** ************* where *********** *** **** diverse. ** ** ******* that ***** ************ *** missed ************ **** ******** as *** ****** ** subjects ********* ******* **** more ****** **** ** more *********** *** ****** to **** ** ****** to *** ****** ** looking **********.

No ***** ******** ** *****: *******

** *** *****,******* ****** ********************* ****** ***** ** people ******* ******* *** scene **** ******* *****. These ********'* ***** **** not ******** ** *** and *** ********** **** Verkada's **** ****.

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All ******* *** **** **********

*** ******* ****** **** miss ****** ********** - meaning **** *** ****** did *** **** ********* a **** *** *******, which ** ********* ** even *** ** ********** what ******'* **** ** is:

  • ******** ****** ****** ***** walking ******* *** *****.
  • ********* *** *** ****** best *********** **** *** at *** **** ** a ***** ********** ********* of **. *** ******* higher ********* *** *********** misses.
  • ******* ****** ****** ********** and ****** ******** ***** in *** *****.
  • ******* *** *** ********* anyone ** *** ***** wearing * ******* ****.

Improvements ** ****** ********* **** ***** *******

********* * **** **** a **** ** * solvable *******. *** ***** is **** ******* ****** did *** ***** ***** systems ** ********* ***** with *****. **** *** be ****** ** ****** new ******** **** ** faces **** ***** **. As ****, ** ***** expect ****** ******** ******** from **** ******* ** include ****.

Harder ********* ** ********* ***** **** *****

***** ********* *********** ****** go **, *********** *********** faces *********** ******. ***** hide *** ****, ****, mouth, ****, *** ***, essentially ************ ******* ** match ** **** *** forehead.

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****** ** ********* ***** can ***** *** ** be **** *** **** sometimes ** ***** ** correct *** ************* *** accuracy, ********** **** ****** scale, **** ** *** reduced.

*** ****-**** ******** **, structurally, ******** ****** ******* where ******* ***********, ****-********** lighting, *** ****** ********** their ***** ********* *** odds ** ********. *** example,*****'* ******* ********** ** already ********** ** **, ** their ********* ***** ***** demonstrates:

*** **** ** ******** works *** *** **** mistakes *** **** ** not *********. *******, ****** control *** **** ** tuned ** ***** **** matches / ****** ** the ********** ** **** that ** ** ****** to *** ****** ** quickly **** ***** ***** users **** ********.

** ********, ****** *********** in ***** ************, *.*., the ***-***** ***** **** examples *** ***** ** face *** ****** ******** - ********, **** *******, wide *****, ***., **** combined **** **** ***** are ****** ** **** facial *********** ******** *** norm, **** **** *************.

Comments (10)

*** *******, *** **** below ******* **** **** 30-40 **********, ******* ** 60-70 **** *** **** subject *** *** ******* a ****.

* ** *** **** I ***** ********* ***** anymore **** ** ******* a **** :)

****** *** ******* ***** recognize ******** ***** **** masks.

*** *** ********* ****** there *** ** *********** that ****** *********** ***** work **** **** *****?

** *** ********* ****** that ********* *** ******* were ******** **** ** we *** * **** test ** ******.

***, ***** *** ****** on **** **** *** can ***** *** **** think ** **** **** but ** *** **** actual ******* ** **** what *******.

* ******* *** ***** were **** **** *** same **********?

***, **** **** *** done **** ***** ******* (that *** *** **** resolution ********* *** ******** and *******), ****** ** also **** ** *** Avigilon *** *******, *** only ********** ******* ***** and ** **** ***** masks *** *** ******** detected.

*********, ******** **** ***-******* the *******, (*** *******) will ******* *** ****** recognition. **** ** ************ noted ** * ****** Insane ***** ***** ****. (Seriously)

********** *** ****** *********** can **** **** **** masks **, *** **** how **** ** **.

******, #*, ***** **** reports ******* ******** ****** our **** *** *********, which ** ***** ** the **** *****.

*** ******* ** **** accuracy ** ***** ** decline ********** ** **** optimization ** *********, ** these ******* ****.

** **** ***** ************* need ** ***** ** how **** ** *****, at *****, ** *** wild, ***., *** **** that ** *** ************* work.

*********, * ******* ******* called ************ ** **** ************ ********** ** ** 95% ******** **** *** with *****. **** **** claim **** *** ******** everyone ** * ***** of ** ** ** (masked) ****** “****** * second”. ****** **********.

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