Dahua Seatbelt And Phone Analytics Tested

By Rob Kilpatrick, Published Mar 02, 2021, 10:25am EST

Detecting people not wearing seatbelts or talking on the phone are 2 areas that have been marketed as being advanced uses of video analytics.

Now, Dahua has included seatbelt and phone detection in their new WizMind line, but how well do they work?

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We tested seatbelt and phone detection in the IPC-HDBW7442H-ZFR, examining:

  • Are these analytics accurate in ideal conditions, e.g., low angles and high PPF?
  • How do harsher angles affect accuracy?
  • How do shadows and glare impact detection?
  • Does it falsely detect raised arms as phones or seatbelts?

*******

** *** *******, **** seatbelt *** ***** ********* analytics *** *********** ******** issues, **** ** ***** conditions (******* ****** *** high ***).

****** *******, ** ***** that ******* ** ***** near *** ******'* **** door, **** ** ***** or *****-******* ********, ******* triggered ******** *********, ******* to ***** ****** **** scratching *** **** ** even ******* *** ******** wheel.

***** ********* *********** *** more ******, ******* ** trigger **** **** ******** clearly **** * ***** to ***** ***, *** triggering **** ******** ********* their **** ** ****** held * **** **, especially ***** ****** **** (away **** *** ****** door).

************, *** ********* **** extremely **********, ********** ** classify ******** (**** ***** incorrectly) ** ********** ***** even ***** ********* ***** find *********, **** ** near ***** ********, ** harsh ******, ** **** distance/low ***, ** **** shadows ** ***** ******* visibility, ****** *** ********* effectively ** **** ******** than ****** ********.

North ******* **. ***** ****** ********* ******

*****'* ********* ** ******* capabilities ****** ********* ** the ******.** ***** *******, ***** *********** ******* "human-oriented *********" *** ********** people ********, **** ****, and ********, *** **** not ******* ******* *********. Additionally, **** ******* ** the ** *** ******* of ******** *** ***** detection, ***** ** *** ********* on *** ***** ****.

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** ********, ** ***** regions,***** **** ************ ******* metadata, ********* *** ******* metadata ****** ****.

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Hands / **** ******** ** *********

** *** *******, ** found **** **** ******** raised ***** **** **** (closest ** *** ******'* side ** *** ***), the ****** ******** **** as ******* * ********. This ***** ** ** scratch ***** **** (****), simply ******* *** ******** wheel ** ***** (******), or ** **** ** the ***** (*****).

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Raised **** ******** ** *****

** ******** ** ********' left ***** ***** ******** as *********, ******* *** inside **** ****** *** face ************ *** ******** as *** ******* ***** on *** *****, ***** here, ***** *** ******* scratches *** ****:

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Aggressive ********* ****** ********** *********

*** ****** ************ ******** to ****** ********, ** conditions ***** **** * human ******** ***** **** difficulty *********** ** ******** were ** *** ***** or ******* *********.

*** *******, *** ******* in **** ******* ***** a ***** ** ***** right ****, *** ** can ****** ** **** with **** *** **** in ****** ******** *** the ***** **** ** shadow.

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** ** ******** *** with *** ******* **** evenly ********, *** ****** incorrectly ******* *** ** wearing * ******** *** not ** *** ***** (both *********) ****** ** is ********* ** *** if *** ******** ** on ** ***.

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**** ********** ********* ********* led *** ****** ** detect ** **** ***** conditions, ** ****. *** example, *** ***** ***** was ******** *** ********** as ******* ******* * seatbelt *** *** ** the *****, **** ****** its ******** *** *** truck ****** *** ********** dark, *********** **** ** outline.

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*** ****** **** ********* to ****** *** ******** subjects ** ******* *********, where **** ****** ** properly ****, **** ** the *** ******* ** at * ***** ***** and *** *** *****:

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"Unknown" ************** ** ******* ******

** *** *******, **** drivers ********** *** ****** from ** *****, **** were ****** ****** ****** classified ** "*******", ***** in *** *** ******** below, **** ****** *** subject ** *** **** can ******* ** **** holding * *****.

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Vehicle ******** *****

*** ** **** ******** the **** ** ****** the *** *** ***** metadata *** **** **** a **** *** ******** in *** ***** ******** tab.

Versions ****

*** ********* ******** **** used ****** *******.

  • ***** ***-*********-***: **.***.*******.*.*, ***** Date: ****-**-**

Comments (16)

**** *** **** ******* article; ******** *********** * waste ** **** ****(** the ******). ***** ** wonder **** *** **** the ********* ********* *****. I ********* ******'* **** to ** *************, ************, and *** ** * retraining **** (** ******)**** bad ****. ** ** don't ****, ******* ******? Now, ** **** ***** beer ****** ** **** liquor (***** ******) ****** with **** ******, ********* and ********, **** *** have ********* *****. *****, I **** ** *** of *** ****** ******. We ***'* ******** ***** any ******. ***'* **** for *** ******. ***** next ******* ***** ** on ********* ** *** purchase **** *** ***** scolded; **** * *******. Stop ******* ** **** these "****** *******" ********. I ****** ** *** analytics *** ********* **** else *** *** ** doing ** **** ***? I *** ******** ***** throwing **** ******* ** the ****** ******* ********(**** both *****; ******* *** defense *** **** * few ***** ** *** process).

********** **** ********** ** investigative *********. **** ***!

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Funny: 1

******** *********** * ***** of **** ****(** *** moment).

** **** ******* ** it ****** ******* **** is *** **** ** tech **** ** ****** about ** *** ***** fairly ********* *** ****** information ***** *** **** it ******.

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Informative: 1
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* ******(** * ***** do) ** *******. * may **** *** **** the ********* ******* ** the ****** *** *** "why". * **** * stab ** * *****..... I **-****, **** ** be **** *** ******* your *******, ***** ***** not ******** ********** *** "why" ** *** ******* other **** *** ****** the **** ****** **** these ****...

**, * *** *** some "***" ** *** very ***** *********...*** ****** to ** ***** ** my ******* **** *** I *** **** **** looked **....

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**** ****** **** ******* Dahua ***** **** **** of ********? *'* **** today, ********* * ***** look ** ** ***.

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**’* **** ******** ** other ********* **** *** and ****** ***********. ** is *** ***** **** we *** ** ** a **** ******* ** that’s *** ** ****** it.

***** ** ******* **** functionality** *****. ******* ** not ** ***** ***** is * *** ********.

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Informative: 1
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*** ************* ** ********* to *** **** ********* as *** ******* ********** and ********* **** *** an **** ****** ******.

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Disagree: 1
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*****'* ******* ******* ** want ** **** ** people *** *** ******* their ********* ** ******* while *******. *** ***** here ** *** **** performance.

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*** ***** **** ** the **** ***********.

****** ******** - ******* a ******** **** * municipality ***** ** ********** in, *** **** ***** augment ***** ******** ********* speed ******* ***** **** ones **** **** ***** warn ** ***** ** the *****/********.

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****** ******’* **** ** be ****** ********, ** ticket ** ******. ******* could “****” ** ** hiding ***** ***** ** raising ***** ****, *** who ***** ****? *** sign ***** *** **** to **** ** ******** accusatory, **** * ******** that ********* *** ********.** it ***** **** ******** 50% ** ****** ******* in ***** **********, * think ** ***** ** helpful.

***** ** *****’* **** work **** *** ****, but * ******’* ** sure **** *** ******.

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*** **** ***** ******* their ******** ********* ***** warning ***** **** **** that **** ***** **** on ***** ** *** phone/seatbelt.

** *** **** ******** going ** ******* ******* it ****** * ****** is ******* * ******** or ******* ** * phone?

***** ** ** *******, seatbelt *** ******* ** a ***** *** ********. As **** ** *** are ***** ** ** one's ***** (*.*., *** say ******* ** ***** 36 *** **** *** actually ***** ** ** 39), ******** ** ** a *******.

*** **** ******* **** you *** ******* ** not ******* * ******** but **** ***?

* ***** *** *** getting ** **** ******** a ******* **** '********: Wear **** ********' ***** I ***** ***** ** fine ****** **** **** this ********** ***** ** well **** ******** ***** that ******* *** *** spend ***** ** *** camera/analytics.

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***** ** ** *******, seatbelt *** ******* ** a ***** *** ********. As **** ** *** are ***** ** ** one's ***** (*.*., *** say ******* ** ***** 36 *** **** *** actually ***** ** ** 39), ******** ** ** a *******.

******** ***** ** * boolean ** ****, *** sign ****** ******* ** not ********* ** ******* you *** ********:

******** * **** ***** flash “******** ******** ** law” ** *** ** not ******** ******* ********. still ** ***** ** effective **** *** ****** it **** **** *** for ***.

*** **** ******* **** you *** ******* ** not ******* * ******** but **** ***?

****** *** *** ****. what ***** *** **? stop ******* ****? ***. if *** ****** *** false ********* ** ********, like * **** **** to **** **** **** triggers * **** ***** alert.

**** **** **** ********** might ** **** **** randomly ***** **** ******* and *** ***** ***** on *** ******/*********.

****’* *** ***** *’** been ******, *** ********** is **? ***** *** false ********/***** ******** **** that ***’** ******?

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Unhelpful
Funny: 1

* ***** ********/***** ******** rate *** **** ** not ****** ****** ******* the ******** ******** ******* in ********* ***** ****** possibly ** ************* ******** **** ****** false ********* *** ********* that ***** ***/*** ** predict **** ***** ** crazy.

*******: ** **** * false ********? ** **** person ******* * ******** and *** ** *** phone?

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** **** **** **** examples ** **** ********* than **** **** *** truck. **** ** ******** like **** ** ** aggressive *** ****** **** accurately ********* ****** *****, what *** ** * false ******** ****?

******, ***/*** ** ***** to **** *********** ********* on *** ****** **********. In ** **** ***** everyone ** ******* ***** seatbelt *** ** *** is ******* * ********, those ***** **** ** wildly *********, **** ** it's *********** *** ****. In ***** *********, *** random ****** ** ***/*** like ****** ***** **** vary ************* ********* ** lighting, ******, ******, ********, etc.

** ***** **** * very ***** ********** ** approach ********* **** ***** to ************* *** ***** I ***'* ***** ** would ** **********.

Agree
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Funny

*** *** *** ********.

* ***** ********/***** ******** rate *** **** ** not ****** ****** ******* the ******** ******** ******* in********* ***** ****** ******** be *********** ** ******** **** random ***** ********* *** negatives **** ***** ***/*** to ******* **** ***** be *****.

*** ***** ***** **** Dahua ******** ******** ** which ********* *** ******** can ** **** ***********, but * ****** **** didn’t ****.

*** ********, **** ***** an *** ******** ** if ***** *********** *** doesn’t **** * ***** view ** *** ***** at * ***? ***** it *** ****** *******?

** ******** *** ******* scenarios **** ***, ************, shutter ***** **** *** would ****** *** ***, (with *** ****** ***** the ********** ******* ** the ***), ***** *** results *******?

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Funny

**** ** **** *** magic *********....

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**** ** ****,***** ******* **** ***** do ****** *********** ** people ******* ** *****.

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**** ** *** *** first **** **** **** oversold **** ****.

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Informative: 1
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Funny: 3

**** ***** *** *** the ********** *********** *** I ** ********** ** relates ** ***** *********** their ************.

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Funny

** *** *******, **** seatbelt *** ***** ********* analytics *** *********** ******** issues, **** ** ***** conditions (******* ****** *** high ***).

**** *** *** ****** false ********/***** ******** **** during *******?

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