UK Facial Recognition Essex Errors Report

By: John Honovich, Published on Jul 05, 2019

Facial recognition trials in the UK have generated significant controversy and debate over the past few years. This week, it flared again when Sky News / Guardian trumpeted that 81% of 'suspects' flagged were false. However, their posts did not analyze the details nor share the original research report. IPVM has.

london MPS police face rec report

In this report, we share and examine the 128-page report including:

  • The new and enhanced methodology that Essex used to analyze these results from more recent facial recognition trials in 2018 and 2019.
  • Why police / human review of matches was so critical and so difficult
  • How the 'accuracy' statistics vary and what the tradeoffs in different approaches were
  • How logs recorded show logistical challenges
  • How UK / EU / GDPR rules for consent complicate the challenges involved
  • China / PRC facial recognition systems contrasted

****** *********** ****** ** the ** **** ********* significant *********** *** ****** over *** **** *** years. **** ****, ** flared ***** ******* **** / ******** trumpeted **** **%** '********' ******* **** false. *******, ***** ***** did *** ******* *** details *** ***** *** original ******** ******. **** has.

london MPS police face rec report

** **** ******, ** share *** ******* *** 128-page ****** *********:

  • *** *** *** ******** methodology **** ***** **** to ******* ***** ******* from **** ****** ****** recognition ****** ** **** and ****.
  • *** ****** / ***** review ** ******* *** so ******** *** ** difficult
  • *** *** '********' ********** vary *** **** *** tradeoffs ** ********* ********** were
  • *** **** ******** **** logistical **********
  • *** ** / ** / **** ***** *** consent ********** *** ********** involved
  • ***** / *** ****** recognition ******* **********

[***************]

Report ********

************* ** ***** ***** Rights ****** *** ******** a ***-**** ******:

Observing ******

*** **** ********* ********** of **** ***** *** here ** ** ********** observe *** ****** ****** recognition *********** ** **** they ***** *** **** happened **** *** ****** were ******* *** ****** recognition *** ********** *******. The ***** **** ***** report ***** *** * trials **** ********:

Problems ********* **** *********** *******

*** ******* ******* *** perhaps **** ********** ******* of *** ****** ** that ********* *** ***** difficulty ******** ********* *******, i.e., ** *** ****** on *** ****** *** same ****** ** *** person *** ****** *********** system **** ********?

** ***** **** *** 6 ******, *** ****** were *** **** ******* the ***** *** *** person ** *** ****** so **** ******* *** person, *** **** ** 8 ** ***** ** times *** *** ****** flagged ** *** ****** the ****** ****** ** the ******, ** *** chart ***** *****:

***** ********* **** *** unreliability ** ****** ********* the ****** ** * key *******:

Sky **** **% *********

*** **% ******** ** Sky **** ******** ** matches **** *** ****** were **** ** ******* dismiss ** ***** ***** matches (*.*., *** ****-**** surveillance ***** *** ******* much ********* **** *** watchlist *****):

***********, *** **% ** wrong ** ***** **** only ** ******* **** were **** ** ** verified *** ** *****, 30 **** ******** ** being *****, *** * rate ** **.*%. *** difference ** **** * matches **** ****** ** be ********. ****** ***, the **** ** '****'.

Debate **** **********

**** *********** * ****** on *** ** ******* the *********** ** ***** systems.

************* ****** ******** **** use *** ***** ******* of ***** ******* ****** them ********** ** **% or ******. *** ****** mentions **** ********:

** **** ****, *** system ****** ******* ********* of ***** ** ****** walking ** **** ***** 6 ****** ********* **** ****** ** be *****. ********** ** this *** (*** ** false / **,*** ***** scanned) ***** * ***** positive **** ** **** 0.3% ** ** '********' of **.*%).

***** ** *****? **** are, ** **** *****. The ******** ******* ***** is **** ********.

Hard ** Visually ******

*** ******* ** **** it ** **** ** visually ****** ******* * match ** ***** ** wrong. ****** **** *****. For *******, ** ********* *********** ****, **** had ** ******** '*************'******* *** ****** *** generating *** **** ******, e.g.:

*** **** *** ********* high ******* ***** ******, not ************ ***** ***** where ******, ********, ******** variances, ***. *** **** it **** **** ** know *** **** ** just ******* ** * screen.

*************, *** ***** *** not ******* *** ******** of *** ******* ** show *** **** ** was ** **** ******* the ********* ***** *** the ****-**** *****.

Logs **** **********

*** *********** ******** * detailed *** ** ************ for *** ** *** test ***********. ** ******** one ******* **** ** front ** * ******* being ********:

** **** ******** ******** mistakes. ******* *** **** interesting ** * ** them ********* **** * minutes. ** *** *****, the ********* ******** ***** whether * ***** ** accurate *** *** ****** one ***** ***** *** ready ** ****** ***** they **** *** ******** processing *** *****:

*** *********** ******* ** that **** ** ***** have ********** *** ********** scores (** *.** *** 0.60). *** ****** ***** that *** **** *********** vendor (***) *** * threshold ** *.**:

*** ******* ********** ***** can ** ********, *** higher ** **, *** more ****** *** ****** rejects ***** ******* *** misses **** ******* *** vice *****. ** **** not ****** ***'* ****** recognition ** ** ****** opine ** *********** ******** but ******* **** ***** would ********* ****** ***** matches *** *** ******* "81%" ***** ****.

Technology ************

*** ****** ***** **** the **** ************ *** the ******* **** ********:

** ******* **** ******** about **** ******* **** used.

Positioning *** *******

*** ******* **** ********* mounted ********, ** ****, as *** ***** ***** from *** ****** *****:

*** *********** ******** ******* is **** *** *** strove ** ******* ******* and ***** ********* **** facial *********** *** ***** performed, ** **** ******* notes:

** *** **** ****, some ****** **** ******** after ******** *** ****** recognition:

China / *** **********

*** ******'* ******** ** China (***) ****** ** such ****** ******* ** facial *********** *** **** it **** *** ******* of *********** ******** ** it ** ************* ********** to ******** *** *********** of ***** *******.

**** ** **** ************** is *** **** ***** PRC ****** *********** ******* work (****** ***** **** been ******* ********* ** the ********, *.*.************************* ***********).

*** ******* **** *** PRC ****** *********** ******* is **** **** **** more ***** ***** ***** on ****, **** ******** data, **** ********* ****** (i.e., ******** ******** **), and **** (** **) legal ************.

*** ******* **** ** that ****** **** *******, especially **** *** *** dealing **** ***** ********** (e.g., ****** **** *** a *** ******* ** a *** ********, ***** PRC ******* ****** ***** have ********). ** ** inevitable **** ***** *** going ** ** ******** mistakes **** **** **** humans ** ******** ****** if **** **** ***** accuracy ** ********.

**********, ***** **** **** and ******* *** ****** about ***** *** ******* performance, ** **** ** hard ** ****** **** how **** ** *****.

UK ****** *********** ******?

***** ******* **** ********** about *** ****** ** facial *********** ** *** UK. ***** *** **** to *** **** (*******, software, *********, ***.) *** the **** ** ******* informed *******, ** ** hard ** *** **** as ***** * '**********' or *********** *******. ***** are ****** *** *** people ***** ******** *** the **** *** ********** involved.

**** ********* *** ****** as *** ********** ******** but *** ********** ** visually ********* ****** *** likely ** ************* ****** given *** **** ****** look ***** ********** ***** the *********** ** ***** quality ** ********** *******, open ****** ***********.

Comments (3)

*********** ******, ***** ***. It's ****** ** *** real **** ***** *******.

******** ******* ****** ***** NEC **** **** ********* by ********** ********** ** Justice *****://***.****.***/*****/*******/******/**********-*****-******-********-*******-**-*************-******-***********-********

** *** ***** **** NN ******* ** ****** face ******** (*****, *** and ****..) ******** ****** in **** **** ********, where ******* ***/*** ******* are **** *** **** position ** *** ** perfect ** ** ********.

** ********** *** "******" (we *** ** ****** to **** *********) ** has **** ******** **** recognition ********** *** ************ performed **** ** ******* NIST *****. 

************* ****** ******** **** use *** ***** ******* of ***** ******* ****** them ********** ** **% or ******....

** **** ****, *** system ****** ******* ********* of ***** ** ****** walking ** **** ***** 6 ****** *** **** 30 **** ****** ** be *****. ********** ** this *** (*** ** false / **,*** ***** scanned) ***** * ***** positive **** ** **** 0.3% ** ** '********' of **.*%).

** *** ************* ** any *** **** ***** negatives **** ******* ** their **********? *** *** this ** ********* **** sounds ****** *****.

** *********, ************* ********* just **** *** ***** numbers, *.*.,**** ** * ********* explanation:

** '*** *** **%' is ****** *****. **** does ** *** **%? How **** ***** *** it **, ***.?

***** *** ********* **** to **** ***** ********* into *******, ** ***** is ** ******** ******** between ***** ********* *** false *********.

* ********** ********* *** ******** ***** to *********** ****, *.*.:

Image result for roc curve facial recognition

*******, ** ************ *********, they *** ******, ** ever *****.

 

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