DHS: 97% Of Facial Recognition Errors Caused By Cameras
The DHS Biometric Rally results found 97% of facial recognition errors are caused by cameras, which reinforces the need for real-world testing, but why does this occur?
In this report, based on IPVM's research, including Facial Recognition Rankings 2023 - Avigilon, Briefcam, Hikvision, IronYun, Oosto, Rhombus, Turing, Verkada, we examine the DHS Biometric Rally, including its procedures, results and the facial recognition errors caused by cameras.
No ******* **** ***
*** **** **** **** *** *** comment ******* ** *** ********* ***** results **** ******** ********* ***********.
*** ** *** *********** ** ********** vendors ********** *** *******, ** ****** comment ******* **** *** ******** ****** comments, *** ****** *&* *************.********** *** ******** ********* **********, ************* and ********.
97% ** ****** *********** ****** *** ** *******
*** **** ********* ***** ******* **** that **% ** ****** ** ****** recognition **** ****** ** ******* (***** below). *********, ****'******* *********** ******** ********* **** ******* ******** ***** **** capture *** ***** ***** **** ******* were ******* ****** **** ****** ****-**** angles *** ****** **** ******* *** match ***** ** ***** ******** ******* and ******* ****-**** ******.
*** **% ***** **** *** ********** by ********* *** ********** ** ***** not ******** ** ***** ******** *** incorrectly *******. *** ****** *********** (****** - *****) *** ** ***** "************** errors," **** ** ** ***** ****** coming **** *** ********* ***** ("****** acquisitions") *** **** *** **** *********** matching ** *** *********, ********* ** 38 *** ** **, ** **% of ****** **** *** ****** *** capturing * ****.
*** ******** ** *** *&*,**** ******,**** ********* ********** "****** ** *********** *** ***** related **** ** ********** **** ******** than ***** **********."
**** ****** **** ***, ** ** our *******, **** ******* ***** *** recognition ***** **** ***** ** ***-***** conditions ******** ** ****-***** **********. ********, accessories **** ** **********, ****, *******, and ***** ******* *** *********** *** matching **** ** *** *******.
** *** *** ********* ******* ****, the ****** **** *** *********** ***** well-lit, ********* ****** ******** *** ******* to ******* ***** *** ************ *** wearing *********** **** ** ****, *******, and **********. ***** ** *** *** Biometric ***** *****, **** ******* ****** to ** ****** ** ****** ************ angles, ********* ** ***** ** ******, and *** ******* **********.
DHS ********* ***** ********
*** *** ********* ***** ** ** annual ***** ********* ** *** ******** Testing ********, ***** ******* ** ****. In ****, *** *** * *********** systems *** ** ******** ******* ** the *****, **** *** *********** ****** dropping *** ** *** ***** ****** the ************ *** ******* *** ****** the *****,********* ** ********* ******.
*** *** ** * ***** *** station, ***** ******* ****** ** ***** people ** *** ****** **** ***** ignoring ****** ** *** **** *** right *****.
* ****** *********** **** * ****** is ***** ***** **** *** ********* Rally.
*** *********** ******* **** ********* ****** two **** **********: ********** (******* *********** time) *** ************ (****-*****). ***** *** systems *** ** ******* *********** **** under * ******* *** ****** ** 2, **** "***** *** *** **** of **** **% ******** ************ *** groups ** * **********."
Biometric ***** **** ************
*** **** ************ ******* ******, ******* IPS, ******, *** ****** *** **** acquisition ******* *** ***** ********, ********, Paravision, *** ******-*** *** **** ******** systems.
************** *** ******-***** ****** *** *** DHS *****, ******************* *********** ******* **** ******** *******,*************** * ******-***** ******, ******* ********** * ******* ******.
** * ***** *******, ****** **** **** ******** * single-camera ******** ***** *** "*****" ***** and * *****-****** ******** ***** "******." The****** *********** ***** ********* ****** *** * ************ **** above **% ** *** **** ********* Rally, **** "*****" ***** *** **** system ** *******. **** *** *** find *********** ** *** "*****" *********** system *** ***** ******* ** *******.
Three-Year ********* ***** **********
**** ********* *** *********** ** *** acquisition ******* ******** ** *** ********* Rally *** *** **** ***** *****. The ******* ******* *********** ********** ** ~91% *** *** ***** ********* ** the *******. *** ********* ***** ******* from **** *** **** **** **** the *********** ********** ***** ~*% ** ~8% **** **** ***** *** ****. The ********* ***** **** ***** ***** is * ~*% **** ** *********** rate **** *** ***** **** ***** through * ********** ** ********* **** 2 ** * ******.
**** *** **** ************** **** (***** of ******* ******* ** ***** *********) and ********-**** ************** **** (***** ** correct ******* ** ***** ********) *** compared *** *** **** ********* *****, there ** ** ******** ** * to ** ********** ******.
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***** *********** ****** *********** ******* *** other *********, ******** ****, *** ******* * ********* *** users ** ******** ******* ***********, ***** metrics ***** ** *** ******** ********* to ****-***** ***********.
**** ******* ******** ********* *********** *** to ********* *** ***** ************* ******* or ***** *******, *** ********** ** real-world ******* ** ********** ** *** Biometric ***** *******.
** ********* *********** ******** ****, ** ******** *** ****** *********** performance ** ******* ************* ***** *** same ********** (********, ************, ******** *****), and *** ****** ******* *********** ****** different *******. ***** **** ******* ******* high ******** ******* **** **** *******, their ****-***** *********** *** ***** **** competitors *** *** ******* ****** ** NIST ****.
*** *** *******, *** *** ************ ********** ****** ********,********* ********** ****** *********** ******.
** *** ***** *********, **** ********* uses ***** *** *******, ***** ****** their ****-***** ************ ***** ******* **********.
*** - ***** ** ** ******** dataset ** **** ****. ***** ********* used ** ******* ** *** *** "special *****", ***** ***** *** *********(*) unique, *** ** **** ***** **** each ****-********* ********. *** ** ***** sending ******* **** * ****** ** real-world ***** ** ** ******.
*********** *******, ******, **** ****-*** ****** and **** * ****** ****** ************** is ********. ******** **** ** *** solutions ******* **** **** *** ***** surveillance-based *** ** **** ***** ***** are ****** ****** ** ***** *************** with ***** ***** *** ** ** worse ***** ****** **** **** ******** (mask, *******...) *** *** ******* **** is *******, ***** ** *** ***** could ** ******.
** ** ******** ** ********** **** access ******* ******* *** *** ************ with **** ******* ** *** ***** satisfying ********** ** *** ******** ********.
* ******* * **** **** ****** but ******* * **** ******* ** I **** *** ***** ** *** of ***** *********. *** ******** *** included **** *** ***** ** **** they *** ** *** ********?
** ***'* *** ** *** ** privacy ******** *** ** ** *** edge ********* ** ******** **** * face *** **** ** *****. ******* at ***** ** ***** ****** * find *** ******* ** ** **** even ** * ** ******* ** low ****** *** *** *****. ** Genetec ***** ** ** ***** ******* setting **** ******** ** ** ******* but ** ******* ** ** **% due ** ****** **** ***** ********. I *** * *********** ********** *** others ********.
* ***** **** ** *** **** independent ******* ** *** **** ******* affect ** *******.
** ***#*,
***** **** * *********** ******* **** were ******** ** *** ******* *** 10 ******** *******. **** ** *** companies **** ******** ******** ******* *******, Corsight (***** *****), ********** (***** *****), and ******-*** (***** *****). ** *** not **** *********** ** ******** ************. Will ******, ** ** **.
*** *** ***** ** *** **** real-world **** ** **** *** ****** Recognition **** ** ******** ** * metric ** ********. *** **** ************* of ****** *********** **** **** ***-*********** license ** ******** ****** *** **** tests *** ******** ** *** ********* against *** ***-*********** *******.
***** *** *** **** ******** * see **** *** *** *****.
*** - **** **** ****** * small ******** ** ****** *********** ************ (39 ** **** *****), *** ***** are **** **** *** ******, ********, biometric, ***. ********* **** **** ****** biometrics. *** *** ***** **** **** not *********** ******* ****** *********** *** Iris *********** ************, ** *** * whole *** ***** ****.
*** - ***** ** ** ******** dataset ** **** ****. ***** ********* used ** ******* ** *** *** "special *****", ***** ***** *** *********(*) unique, *** ** **** ***** **** each ****-********* ********. *** ** ***** sending ******* **** * ****** ** real-world ***** ** ** ******. ** some *****, ** ***** * ******** training **** *** **** ** *** or **** ********, *** **** ********* bias, ****** ** *****, ****** ****, etc. **** *** ********** ****** **** included ** ***** ******** ****; **** they *** ***** ****** ***** ***** and ******?
*** *** ***** ** *** ** the ****, ******** ***** ** **** today; *** *** ** ***** **** a *** *** **** **** ** need.
* **** *********** ***** **** ****** reinforce **** ** *** ***** **** guessed, ** ** ******* ***** **. The ** ******* ********** ******* ********* results, ******** **** **** *** ** fed ******** ***** ** ********** ******* (and, ***** *** ********* ******* ******* important, **** **** ********* ****** ** sufficient ******* ******** ** ****).********* *** job ** *********** *** *** ***** is, *********, ** ****** **** ***** of **** ******* *** ********.