Avigilon UMD / UAD Tested

By Rob Kilpatrick, Published on Oct 14, 2020

Avigilon's Unusual Activity Detection and Unusual Motion Detection claim to "uncover events that may go unnoticed", but how does this claim stand up in real world scenes?

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We tested Unusual Activity Detection and Unusual Motion Detection for over a month, examining:

  • Do they both alert on proper unusual activity or motion?
  • Do they miss unusual activity in the area?
  • Do either UMD or UAD false alert?
  • How easy are UMD and UAD to setup?
  • Can they be trained to not identify usual activity if it considers the activity unusual?

*******

***** ** *** *******, Unusual ******** ********* (***** uses********'* ** *********) ********** ******* ** atypical ******** ** *** scenes ******, ******* *** out, **** **** ********** false ****** *** ** parts ** ****** ***** detected ** **** ** due ** ********* ** parked ******** ** *** tests.

*******, ******* ****** ********* (which **** ***** *** data *** ** *** most ******* ******** ******* perform ****) ******** **** significant ***** ****** ****** by *******, **********, *** lights ***** ****** ** and *** ** *** testing, ****** ****** ** fundamental ************ ** ***** motion *********, ***** ** is ***** **.

*******, ******* *** *** UMD ****** ***** ** simply **** ******** ****** as *** *******, ** activities **** *** ******* but ********** (**** ** emptying ***** **** * dumpster ******) **** ******* UAD/UMD ******.

Avigilon ********

******** ******* **** ******** on ***/*** ***********:

***** *** *********, *** and ***, *** ******** to ******* **** ******** events. ***** *** *** events **** ** ******** should ****** ** ***** for *** ***** *** meant ** “**** ******” or ************* *** **** are ********* ** *** Focus ** ********* ********* (FoA). ** *** **** there ****** ***** ** a ****** ** * secure **** **** *** up ** ‘****** ** Area’ **** – ** is ********** *** ******** and ***** **** ** very *** ***** *********.

******** ******** *** ***** of ********* ********* ** the ******* ***** ** deliver ******* ******. ***** events *** ************* *** therefore * ****/***** ** not ******* ** *******. As ***** ***** ***** events **** ** ** more ******** *** *** meant ** ** ******** quickly ** ** ******** in *** *** *********. Users *** *** ***** judge – *** ** providing **** **** ********* (and *** ******* *** them ** ******* **** cameras).

Unusual ******** ********* **. ******* ****** *********

*** *** *** **** similar ****, *** *** uses *** **** ******** analytic **** ***** **********'* ** *********(*.*., ***, *****, ****, classifications) *** *********** **** is *******, ***** *** uses ***** ****** ********* events, ***** *** ** nature **** ********. ** our *******, ***** *****, UAD *** ************* **** accurate **** ***.

******* ******** ********* ** available **** ***** ******** *******. *** ** ********* on****,***,***,****, ***** **** ****.

Accurate ******* ******** *********

******* ******** ********* ********** triggered ** *** *****. In *** ******* *****, it ********** *** ***** as ******* (**** * yellow ******** ***) ** they *** ****** ****** in **** ****.

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*** **** ********* ** unusual *****. ** ** area ***** ***** ******** normally ****, ** ***** the ******* ******* ***** as *******.

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*******, ****** ******** ** unusual ***** ** *** scene **** ******* **. In *** ***** ***** below, ******** ********** **** from *** ****, ******, to *** ******* *** to *** *****, *** rarely ***** *** **** near *** ****** ****.

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People ******** *** ********** ******* ********

***** *******/**** ***** *** properly ********, ****** ******** at **** ***** ******* the ***** **** *** identified ** *******.

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

** **** *********, ***** of * ***** **** considered * *** ** an *** ***** *** were ******* ** ** unusual ********.

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************, **** ****** *** considered * ****** *** created ** ******* ******** event. **** ******** **** once ****** ******* ***** of *******.

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Normal ******** ********* ********** *******

****** ******** **** ** a ***** ******* ******* the *** ****** *** day *** ******* **** sometimes ********** ******* ****** not ********** ******* *** that **** ** *** day ** **** ** the *****.

Unusual ****** ***** ***********

******** ****** ** ** area *** ********* ******* on **** ** * person ****** ** * low ******* **** ** the *****.

False *** ****** ** ******* *** *** **********

*******, ***** *** ****** on **** ******** ***** motion *********, ** ******** from ******** ***** ****** caused ** ******** *********** not **** ** ***.

*** *******, **** ********** highlighting ***** ** *** scene ***** ** *** typically *** ****** ********* UMD ******.

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** *** ******* ***** cast ** ***** *****:

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*******, ***** ***** ******* (e.g., ******* ****** ** and ***) ****** *** events.

Significant **** ****** ** ***** *****

**** ******* ******** *** Unusual ****** **** *********** periods ** **** ** learn *** ***** *** start ****** ******** ******. UAD ***** ***** * week, ***** *** *** require ** ** *** weeks. ****** *** ***** is ******** *******, ****** occurrences **** ** ******** walking ******* *** ***** below *** ******* ***** alerts:

******* ** ********'* ***** self-learning *********, ***/*** **** a ******** *** ***** shows ******* ******** ********:

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No ****** ******** ** *** ** ***

**** ******* ****** *** Unusual ******** ***** ******** in *** ***** **** a *** ****** ** time. ***** *** ***** is ******* *** **** will **** *** ****** of **** **** ********* deem *******, ***** ** no *** ** ***** the ********* ** *** trigger ****** ** **** it ********* ******* *** the **** **** ***, such ** ****** ******** trash **** *** ******** shown *****.

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Focus ** ********* *********

***/*** ****** *** ********** to ********'* ***** ** Attention *********, **** ****** highlighting *** ********** ******'* hex ***** ****. ********* can ****** ***** ** view *** **** ***** or ****** ***** **** to **** **** *****.

** ***** **** *********** unusual ****** *** ******** detection ****** ** **** visibly ********* **** ******* a ********* ***** **** with * *****-****** ****** because, ** ******* ** ******** **** testing, *** ****** *****/******** are *** ********* ** a *** **** ******* the ******* ********* ** a ******** ********. ********, other ******** ****** **** facial *********** *** *****-***** the **** ** ***/***, which ****** ** *******.

Simple ***** / ***

**** ****** ***** ** required *** ***/***. ** H5A *******, *** ** enabled *************. ** ******* supporting ***, ***** ****** toggle ** ** **** a ********.

****** *** ***** ** Avigilon's ***** ** ********* interface, *********** ** * lighter **** **** ******* events *** ********. ****** in ******** ***** *** be ***** *** ***** search, ******* ** ***** analytic ******, ** *** be ********* ** *** timeline *** ****** ******.

*******

******** *** *** *** are ******** **** ********* of ******** ******* ******, no ********** **** *** required.

******** ****

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

  • ******** ******* ******: *.**.*.**

Comments (4)

Avatar

Ryan Ritter

Avigilon | 10/15/20 08:23pm

************, **** ****** *** considered * ****** *** created ** ******* ******** event.

***** ** *** *** Spider *** ********* ** working!

** *** ***********, * am ******* ***** *** truck ***** ***********. ** you ********* *** ****** in **** ******* *** get **** ***** ** parking *****/***** ****** *** end ** *** **** ramp ** **** ******?

****'* ** ******* ***** for **** *** **** triggered **, ********** ** the ***** ******* * couple ******* ***** ****. Reminds ** ** *** initial ******* **** ** showed ** *** **** a ****** ***** *** with ***: ********* ** a ****** (*****, ***, so **** ****'* **********) walking ** * **** and ******* ** *** out, ********* ** ******.

***** ***, *** ****** it ********* *** **** covered *** **** *** the ****** ********** *** areas ** *** ****. So ** ***** ***** and **** *********** ** the ****** ****** ******* the ****.

***** ****. ******* ******* through **.

Avatar

Ethan Ace

IPVM | In reply to Ryan Ritter | 10/15/20 09:17pm

** ******** **** ****** drive ****** **** **** exact ***** ***** ***. The ******* **** **** does ************ ** ***** is ***** ******* ********** from **** ********* ** the ****** ** *** night. **'* ******** ** could ** ****** ** the **** ** ********, though, *** ** ******* pretty *******. *'* **** wondering ** ** ***** become **** "******" ***** more ****, ** *** camera ******* **** ******, etc.

Avatar

Ryan Ritter

Avigilon | In reply to Ethan Ace | 10/15/20 09:25pm

* ***** ******* *** answer ***** ********** ** yes, *** **** *'* unsure ** ** *** many ********* ** ***** take *** *** ***** to ******** ** ******.

**** ********/******** ** ***/*** is **** ** ** wishlist *** ***** ********. I ***** ****'* ****** what **** ***** ** to ** ****-*****.

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

Michael Miller

In reply to Ryan Ritter | 10/15/20 09:43pm

****, **** ** * message * ***** ** happy ** **** ***** UMD *** ***.

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