Dahua Face Recognition Camera Tested

By: Rob Kilpatrick, Published on Oct 15, 2018

Dahua has been one of the industry's most vocal proponents of the value that AI creates:

As part of this, Dahua has released a facial recognition camera, the DH-IPC-HF8242FN-FR, claiming:

Artificial Intelligence at the edge – performing complex real-time facial recognition and facial feature comparison

But can this new model really deliver face recognition in real-world scenes? We bought and tested the HF8242 to find out, answering these questions:

dahua face recognition ipvm

  • How many false negatives or positives to expect?
  • How well does the camera handle subjects looking down or away from the camera?
  • How does recognition perform in low light?
  • How does recognition perform in <1 lux with IR?
  • How does recognition perform in WDR scenes?
  • What imaging and environmental issues impact recognition performance?
  • How well did the camera capture demographics such as age, gender, facial hair, and others?

***** *** **** *** of *** ********'* **** vocal ********** ** *** value **** ** *******:

** **** ** ****, Dahua *** ******** * facial *********** ******, *****-***-********-**, ********:

********** ************ ** *** edge – ********** ******* real-time ****** *********** *** facial ******* **********

*** *** **** *** model ****** ******* **** recognition ** ****-***** ******? We ****** *** ****** the ****** ** **** out, ********* ***** *********:

dahua face recognition ipvm

  • *** **** ***** ********* or ********* ** ******?
  • *** **** **** *** camera ****** ******** ******* down ** **** **** the ******?
  • *** **** *********** ******* in *** *****?
  • *** **** *********** ******* in IR?
  • *** **** *********** ******* in *** ******?
  • **** ******* *** ************* issues ****** *********** ***********?
  • *** **** *** *** camera ******* ************ **** as ***, ******, ****** hair, *** ******?

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

Good / *****

*** **** ******** ****** of *****'* ****** *********** camera ** ****, *** small ******* *** *** traffic *****, *** ****** generated *** ***** ********* minimizing *** ************** ****** in **** ********** ****** recognition *********. **** ** did ********* * ****, overwhelmingly ** ********** ** accurately, *** *** *** recognize ********* ******* ** faces ** **** ***** "AI" ******** ****, *.*.,********* ********** *********** ******* as **** ******.

Bad / ******

*******, *** ***** **-***-********-** had ******** ****** ****** it **** ********* ** recommend *** ******/**** ********** use.

  • *** *********** ****:*** ****** ****** ** recognize ~**%+ ** ******** whose ***** **** ********, due ** ******** ******, with ***** ** *********, subjects ******* ****/****, *** low ***** ******* *** majority ** ********.
  • *********** ********** ********** **** looking ****/****:** *** *****, ****** confidence ********* ** ** least ~*-**% **** ******** looked **** ** **** from *** ******, ****** it *** ******* ***** in ******** *******.
  • *********** ***/*** ***** ********** reductions:************, ********** ******* ** least *-*% ***** **** difficult ******** **********, ********* simple *** ******, *-* lux *** *****, ** dark ****** **** ** on.
  • ******* ** ** *********** under * *** (******* IR):***** * ***, *********** became ******, **** *** majority ** ******** ******. At ~*.* *** *** below, ********* *** *** work ** ***.
  • ******** ********* ** ******** recognition:*** ****** ******* *** person *** ******* * times **** *** ***** of ******* ** ******** scenarios, ***** * ***** database ** ***** ** people ** * ***** office. ** ****** ****** installations, ******** ** ****** to ********, ** ********** subjects ******** *** ********** that *** ****** **** look *****.
  • ******** ********* *********** ***********:*********** *********** ** ******** was ********** *****, **** male/female, *******/** *******, *****/** beard, *** ***** ******* incorrect **** ** *** time.

** ****** *********** ****** in **** *****:

*******

*** ***** **-***-********-** ***** for ~$*,*** *** ******, not ********* ****.

Adding ****** ** *** ********/*********

********' ***** *** ***** to *** ******'* ******** through *** *** *********. Users ****** ** ***** for **** ****** ** be **********, ***** **** and ***** ***** ***********, and **** ****** ** to *** ******.

**** **** ******** ****** must ** ********. ***** is ** ***** ** simply *** ****** ** tagging **** ** *****, for *******.

****** *********** ****** *** be ******** *** *** NVR, *** *** ******** on *** ****** ******, since ******** *** ****** on *****'* ****. ***** recommends * ******* ****** of ***, *** **** series (*** ******), ***** allows ***** ** ****** for ******** ********' ****** images. ******** **** ***** searching *** *********** ***********, but *** ******** ******.

demographic information search via nvr

Missed *********** ******

****** *** ******* *** camera ****** ** ********* about ~**% ** ********** subjects **** ****** ******* the *****, **** ***** Dahua's ******* ********** ****** of **%.

*** **** ******** ***** of ****** *********** *** subject ****** *****. *** example, **** ******** ****** down (** **** ** when ******* ********), ********* was ****** **** **** 50% ** *** ****.

frequent missed recognition due to head tilt

************ ** *** ******** face **** ****** **** missed ************, **** ** indoor, *** ******, *** when ***** *****'* **** exposure ******* ***** ******** to ********** ******** ** faces ** *** *****. For *******, ** *** image *****, *** *******'* facial ******** *** *********** by ****** ****** ******** in ***** ** *** with **** ****** *** in *** ****** ****** (though **** ******* ***** still *******).

https://user-images.githubusercontent.com/11630256/46947956-a23f3500-d0a6-11e8-824a-01a3d7015b21.png

~90% *********** ********** ** ***** **********

****** *********** ********** ******** about **% ** ***** conditions, **** *** ******* looking *******, *** ***** evenly ***, *** ****** mounted ** *** ***** recommendations (~*' ****, ~**° downtilt).

Head *******/******* ~*-**% ********** ********

****** *******, *** ********-** ************ had ~*-**% ***** ********** rating **** *** ******** face *** ****** **** or ** *** ****, causing * ******* *** people ******* ******* *** scene ******* **** ** their ***** ** **** or ******* ***** **** away **** *** ******.

head titled

Recognition ********** ***** ** *** *****/****/*** ******

*******, ******* ********** ******* confidence ** **** *******. For *******, *** ***** scenes (~*-* ***) ********* confidence ** ~*-*%.

low light

** *** ****** ****** (<1 ***) ***** ******** integrated **. ** **** scene ********** ******* **** ~91-93% **** ****** ** and **** ** **-**% with ** **.

external ir illumination

*** *** ******* *******, dropping ** ~*% ** a *** ***** **** a ********** *** ** ~3000 **. *** ******, shown *****.

wdr

Frequently ********** ************

*** ***** **** *** camera ******** ** ******** various *********** *********** **** faces *** ********, *********:

  • ***: * ******** *** is ********, *** ** searchable **** ** ***** categories (******, *****, *****, middle ***, ***)
  • ******/****
  • ****** **********: *********, *****, happy, ***.
  • ******* ****: ***/**
  • *** * *****: ***/**
  • ******* * ****: ***/**

** *** *****, ***** identifiers **** ********** ********* on *** ******, **** performance ******* ****** *** mounting ********* ******, ** various ******, ***** ******, WDR ******, *** *****, etc.

*** *******, *** ******* below *** ********** ***** as **** ** ***** old (****** ***: **), with *** ******* *******, and **** *** ******* a *****.

age beard

glasess

**** ******** **** **** frequently ********** **** ******** as ****** *** **** versa:

female

Multiple ***************

**** *** ****** ** ~2 ***** ** *******, the ****** ********** *** registered ****** *** ******* four *****, ***** * database ** ~** ****** in * ***** ******.

** ****** ******* **** more ********** *****, ***** issues *** ****** ** increase ** *** ******* two ****** ****** ******* increases **** ****** **********.

Full ****** ************* **** ********* ** **** ***

** ***** ** ****** all ********** ******** ** the ******, *** ***** IVSS *** ** ******** (~$4,500 ****** *** *** channel/1TB). **** ******** ********* for *** ********* ** a ******** ********** ******, specific ********** *******, *** more. ********* *** ** done ** * ***** NVR **** *** ********* tab, *** ** ******* to *********** *********** ****, with ** ******** **** search.

***** **** **** **** capability **** ** ******** in * *** ********, not *** ********* ** North *******.

Typical *** ****** **** ******

*** ********-** ** ******* to ***** ***** *** models, ****** ******** ****** and ******* ** *********** additional ********** ** *****.

similar construction to other box models

Versions ****

*** ********* ******** **** used ****** *******:

  • ***** **-***-********-**: *.***.*******.*.*, ***** ****: 2018-07-09

Comments (21)

* *** **** ****** this ** ***** ********* testing, *** *** ***** facial *********** ** ****** of *****?  ******* ** and ****** *** ****** them ******, *** ** Asia, ***** *** *** less ****** ** ***** and ******* **** ******* of ****.

****, ****** ** ***** in *** *****......* ****** have ***** ********** ** much ****** ** "***."

** *** *** **** this ************, *** **'* a **** ***** ** consider. **'* ********* ****'* come ** ** *** past, ** ****.

****** *** *** **** committed ** ***** ****** ya ****.....:)

******* ** ******* ***** unhelpful, *** ** ****?

**** ******** **** ******* heavily ** ******* ****** a ******* **** ** capturing ****** ******* ******. There's **** ****** ** photography *********** ********** **** prerequisite *****.

******* *********. *'* ******* to **** ** *** were ** **** ****** at ********* ****** *** then ****** ***** **** the ******** ** *** would *** **** ******* say **** ****** *** looking ** *** ***** or **** ** **** walked **** *** ****. 

**** ***********, ***** ** I *** ** **** shirt?

****** ******** ********* ****** with * ****** ******* their **** ** ******* directions **** **** **** compared ** * ****** reference. ****** *** ******** structure ******* ******** ****** may ** ** *****.

*'* ******* ** **** if *** **** ** take ****** ** ********* angles *** **** ****** those **** *** ******** if *** ***** *** more ******* *** **** people *** ******* ** the ***** ** **** as **** ****** **** the ****.

* ****** **** ***** a ******* ** ** head ****** **** *** a ******* ** ** looking ** *** ****** and ** ****'* **** a ********** **** ********* image * ****, ** would ***** **** * ~90% ********** ****** ** my **** *** ******* seen ****** *** ****.

head tilt vs straight 1

**** **** ******* **** the ****** **** ** head ****** ****, ********** rating ******* ******* ** what ** **** ** the ****** *** ** was *** **** *** both ******.

head tilt vs straight 2

* *****, ** ** just ** ** ** the ****** ***** ****** divergent ** ***** ********?

****, *** *** **** to **** ** *** Facepro ****** ** *********.  The ******** **** *** mentioned ** *** *********.  Facepro **** **** ******** AI ******* ** ******* learning.  *****, ** ** able ** ****** **** variations ** **** ******.

** ** ************* *** *** not ****** * ******** person *** *** **** to *** *****.  *** need * **** ***** to *** **** ** the *****.

 

 

*** *** **** ***!

*'* ******* *** **** stacks ** ******* ***** companies ***** **** (*** Hikvision ****** *** ********** enlightening), **** ** ********* or *******.  **** *** Axis ***********, *** ******** on * *********** ***** out?

**** *** *** ***** Amazon ****** *********** ***, I'm ******* ** *** what ****** *** "*******" in *** ********.  *'** dealt **** ********* **** are ******* *** **% accuracy **** ** *** security *****'* *********, *** other ********* ***** ***** 90% ** *******.

**** *** **** ****. This ********** ***** *** as * ****** ********** 2D ******** **** *** the ******** ********* ** uncontrolled **** *** ********. For ********* ************ ************, I ** ****** ******** simple ** ** ** viable. *** **** ********** and ********** **********, ******** by ******** ****** ** same ********** ******? ****. But * ** ********* that **** "**** ********" and "**" *** ******* a *** *% *** in ** ************* ************ engagement. ****** ******* (*.*., RGB-D) *** ******** ** achieve *** **** ** results **** **** ** acceptable *** *********. 

**** ******! * ***** like ** *** * comparison ******* ******** ****** recognition *********, **** *****, Hikvision *** **** (**** Ayonix). ** ***** ** great!
****** ****** ** ** 3D ** ******** ** any ******* **** ******.

 

***** ***********...***** ***.  ** it ********* **** **** that ****** *********** ********** is ** *** ******* and *** *** ***** for *********?  ** *****'* technology * **** ***** step ** *** ***** direction?  **** ********** ********** follows *** "********** ***" theory, *** ** **** the ***** ***** ******** by ***** ********? 

**** **** **** **** this ** *** ****** of ****** ********** ***********?   When ********* ******* ** come ** ***, ** became **** ******** *** easier ** ******, *** it ***** **** *** appear ** ****** ***** confidence ***** **** *** users. 

** *********, ******* **** facial ***********, ***** **** confidence ******, **'* *** hard ** ******* **** every ****** **** ******* these ********.

*********** ****** - *** highlights **** ****** *********** (applied *************) ** ******** coming **** *** ********** if *** *** *** get * ******** ** limited ********** ** * $1k ****** **** * vendor **** *****.

**** ** *** ****** here (**** ** ***** confidence *** ****** *****) are **** *** **** of ******* ********** ** lower-end ****** *********** ***** fairly ******** ******* - and ****'* ***** ** comes **** ** **** application, **:

- ** *** **** cooperative/ ********* ******** ** an ***** ******* **** (who *** ** ******** to **** ** ****** in * ********** ***, eg. *** ******** ****** to *********), ** ***-*********** / ******* ******** (****** capture, *** ******** ********* and *** ******* *********)?

- ** *** ******** purpose **** *** *********** / **** ********** / general ******** (***** ***** negatives ****'* * *** deal, *** *** *** play **** ********** ****** - ** ** ** for * ********* ************** / ************** ***** ***** positives *** ***********)?

** *** ***** *****, even *** **** ****** recognition ****** *** ** defeated ** ** ************ scene ** ****** **** the ****** ** ***** or ****** **** ** avoid ****. ***** *** some ***** ********** *** drawing *** ********* ** the ******* ** **** at *** ****** (*** most ******* ***** ******** *********** ********!) **** *** ******* this ** **** ******.

** *** ****** *****, you'd ***** *** * camera **** **** - or ****************-***** ****** *********** ******* - ** ********* *** a ******** ********* ************** application (*'* ****!).

**, * *** **** test **** **** ***** in ***** ****. ******* my ******* ** * bit ***** ******** **** I *** ** *** Kilpatrick ****.
******* ******* *** *******. What ** *** ******* is *****. *** **** show ***** **** ***** will ** ******** **** will *** **** ********* systems, ******* **** ** IPVM ***. ** **** my **** *** **** under ********** ********* ** understand *** **** ******* so ********* **** *******. Main ****** ** **** users ******* **** *********** works ***** *** **********. Unfortunately ***, ** *** quite ******** ******* ***** for **********/*******/*****/**** ** *****/*********.

** **** * ***** agree **** **** ****** comment - ********* **** kind **** ** ***** minimal ********** ***********.
** **** *****: * have ** *** **** I *** **** ********* how ****** ** **** be ********. ** *** my **** ** * have ** ******* **** under ********** *********** **** AI ****** *** ***** 1% ***. ******* ****** under **********. *.*. **** of ******** ******* **** face ***** * *** different ********** **** **** sense *** ******** * lot ******.


** ******* (****** ** shorten ** ********):
******** *********** (*** ****** in ********):
**** ******* ** *** frontal ***** **,*%. ***** up ** ********** ***** 22,5deg ***** **%.
******* ****** ** *** or ***** ***** **** the ****, *** ** compare ***** ****** **** angle ** *** ** nonsense.
(**** ** *** ***** that *** *** ******* left ** *****, * deg ** ******** **** camera).

******** *********** (**** ** recognized ****** ** ********), 452 *****: **% (**** 18 ***** *** ******* detected ** ****** ** database).

**** ******** *** ******** depends ** ********* *** Similarity *********. ***, ***** has ** ******* *** 82, *** *** ***** application *** **** *** your ***. ** ** VERY ********* ****** ** get ********** *******. ******* above *** **** **** 85. ***** **** *** clear **** ***** ***** to ******** ******** *** positive *********** **** ** 87.
**** *** ******* ***** you **** *** ** Similarity ****** ***** *** high ** *** ***:
******** *********** (**** ** one **** **** ** display *** ** ********):
**: **% - **** 80% *** ******* ******** as *** ** ******* fro **** *********.
**: **%
**: **,*%
**: **,*%
**: ***% - ******* this *** ****** *** for ********* *********** ***** threshold *** ****** ** DB ****** ** ** hig.

***, ** *** **** person ******** **** ******** resolution ****, *** ** must ** ****** **** increasing ********** ********* ** reach ****** ******** ****.

** *** *** **** test ** **** ***** 90% ??

**** ** ***** * found **** *** **** significant ****** ***** ******: resolution, *******, **** ** scene.
********** ** ******** **** really ****** ** ****** recommended *******. ** *** forget **** ****** ** just ***** ** **** recording ** ****** ******** to *** **** ******* part ** ***** ** not ****. ** **** it ******* **** ****** must ** **** *>****. This **** ******* **** scene ****** ** *** this ****** *** ***** 2,9-3,3m.

******* - ********* *** influence ** ******** ****. Found **** ***** ***** blur **** ******** **** influence ** *******. ** fact ******* ***** **** using */*** *** ******* is *********! ** ** will *** **** ***** IR *** ******* *******. However *** *** ***** reason, *** *** **** reason ***** ** ***** working **** **** ****** shutter.

** **** ***** *** things *********** *********** ** use ****** *** **** than ***** **** ******** axis, ***** ****** ********** between ******* ********* *** camera ****** ***** **** much *****. ******* **** camera ** ********* ** ceil **** ** ********* low. **** ** ***** why *.*. ***** ** current ******* ** ****** for ** **** ** problematic. ***, *** **** cases *** *** **** datasets ** ****** **** top.

*** ** **** **** database ** *** ** complicated ** ** ******* people ****** (**** ***** can **** **** ******* there, * *****). ***** are ****** *** ******** in **** ******** ** far ** *** **** opened *** *** **** you *** **** ****, sort, ***** *** ****** into ********. ****** ****** solving **. ** ** you **** *** **** people **** ** ******** from **** *** **** to *** ** ******** all **** ******* ****.

**** **** ** ***** plays ****. **** ****** is **** ** ***** at *** **** ** faces, **** **** **** to **** ** ******* minimally *,**. *.*. ** means **** **** **** must ** ****** **** time ****** *** (**** again...shutter/iris/light)! ** *** *** have ******* ***** (** any). ****** ***********, ******* time ********** *******.


****** **** ** *********** of ** ******* ** not ** **** ** to *** *** **** motion *********, ** ***** unbelievably ******, ********** *** Police. * **** ** note **** ********* **** and *** ****** ****** have *********** **********. **** I **** ** **** especially *** ******** *** - ******** *** **** provide ****** *** ** NO. ** ******* ****** also ** ******** - "Show ** ****** ******* to **** *** ** my *****" *** ******** can ** ******* ****** similarity ********* *** ***** number ** *******. ** then ** *** ********* if *** ******* ********** on **% ** **%, cause ** *** ************ limit ****, **** ***. and **** *** ******* set ** ******* ****** similar ******** ***. ** then ***** ******* ** thousand ***** ** ***** just *** **** ********* is ****!

*** ***** ** ******** about **** ***** ** race - *** **** you **** ** **** not **** *** ****. It ** ****** ** training ******* *** ****** network *** ******* ******** are *** *** ** all *****. ***, ****** can **** ***** * lot ** ****** *** this ** *** ****.

*** * ******: ***** datasets **** ***** **/** community, *** *********. ******* above ********* *** ********* FERET ********. ******** ****** on *******, ****** ******** to ****.

******* * **** ***** test ***:
****** **** ***-*******-**
****** ******* *.***.*******.*.*, ***** Date: ****-**-**
*** ******* **.*.*.******
***** ******* **.**(**.*.*.******)
********* ******* *(*.*.*(**.*.*))-*(*****)
**** ******** ******* **.*

*******, ****** *** *** detailed ********. *** *******:

*** **** **** ***** real ***** **** ** mistakes **** **** *** such ********* *******

**** ****** ** **** users ******* **** *********** works ***** *** **********. Unfortunately ***, ** *** quite ******** ******* ***** for **********/*******/*****/**** ** *****/*********.

***** * ***** **** enforcing '******** ******* *****' will ******* ***********, ************** 'real *****' *** *** going ** ****** ****. Confining ** *** '******** limited *****' ********* ********** and **** ** ***** and ******** *** *** where ** *** ** used. **** ********?

** ****,

******* ***** ** ********* is ******** *** ** interested **. ** * guess '**** *****' *** those *** ***** **** system **** **** ****** for **** *****. ** opinions ** ** **** others **** ********** ** in **** *****, *** has *********** ******. ***** is ** ****** ** inflate ** ******* *** on ***** **** ** no ****** ** *** the ***** ** ****. Simply **** **********, ** for ***** *** *******, should ** ***** ***** about ************ ******** *** it. *** * **** it *** **** **** of **** **** ** application ********.

** **** ** **** for *** ****** ****** called "**" - ********* dep. *** ****** *** able ** *** ******* of ************ ***** ** not ********** **** *** documentations ** **** ****, sometime ************ *** ** frighten ******** ****...

*.*. ** ** ***** that * *** *** get **** ***** **** Hikvision ** ****** ***** you **** ****** ** unsucesfull. **** ************* *** the ******** **** *********** and ******* ****** ******** I ** ********* **** it ** ******** ** make ** **** **** ;-)) ***, *** **** answer **** ****** ****** be **** **** ******** - ************* ** ***** in ** **** ***/*** power, ***** ***** ****** cost. ** ** *** where ** ***.

** ******* *** **** engineers ****** ******** ******* should **** * *** how ** ********* ** reasonable ***, ****** ** get **** "*******" *** what *** ******* ******* called '**'.

*** ***** *** ** stop ********* ***. ** inflate ************ ** **** systems ** ************ "***** cuts".

*** ***** *** ** stop ********* ***. ** inflate ************ ** **** systems ** ************ "***** cuts".

*******, * ** ***** with ****.

* **** ***** **** this ********* **** ***:

******** ************ *** ** frighten ******** ****...

*** * ** ******** here:

** ******** ** ** tell ****** **** ********** is ** **** *****, but *** *********** ******. 

** *** ********** *** 'in **** *****', ** would *** **** ***** 'application ******'. *** **** these ******, *** ****** is ******* ** **** few ********* **** *** willing *** **** ** conform ** ****.

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