Deep Learning Tutorial For Video Surveillance

Author: Brian Karas, Published on Oct 17, 2017

Deep learning is a growing buzzword within physical security and video surveillance.

But what is 'deep learning'?

In this tutorial, we explain deep learning specifically for video surveillance covering:

  • Traditional video analytic approaches
  • Machine learning vs deep learning
  • What makes learning 'deep'?
  • How deep learning can help analytics
  • The role of training
  • Examples of training for people and guns
  • Example of training for men vs women vs old vs young
  • Filtering alarms With deep learning
  • Training data not disclosed
  • Potential Problems Across Regions
  • Hardware Requirements
  • Evaluating Deep Learning Products

**** ******** ** * ******* ******** ****** ******** ******** *** video ************.

*** **** ** '**** ********'?

** **** ********, ** ******* **** ******** ************ *** ***** surveillance ********:

  • *********** ***** ******** **********
  • ******* ******** ** **** ********
  • **** ***** ******** '****'?
  • *** **** ******** *** **** *********
  • *** **** ** ********
  • ******** ** ******** *** ****** *** ****
  • ******* ** ******** *** *** ** ***** ** *** ** young
  • ********* ****** **** **** ********
  • ******** **** *** *********
  • ********* ******** ****** *******
  • ******** ************
  • ********** **** ******** ********

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

********

**** ******** *** ****** * *** ** ********* ** *** security ******** *** *** ********* ** ******* ******* ** *******-*** analytics ********. ** ** ********** ** ** *** ****** ********* of ********** ************ ** ******* ******** *** ** ***** ******* in * ******* ** ********** ** **** ********* ****** ********** and ******** ******* ****-***** ******** *** **********. *** *** ******** of **** ******, ** *** ********** **** ******** ************ ** the ******* ** ***** ************, ****** ********* *****.

Traditional ***** ********* **********

***** ** **** ******** *** ** *********, ******* ********* ****** on **** ***** *********** ** **** ******* ** ****** (*.*.: people *** * ******** ****** *****, ******** *** * **** aspect *****), *** ****** *********** ** **** ******. *** *********** step ***** ****** ***** *** ****** *** ******* ****, ** that *** ****** ***** **** ************* ****** ******* ***** *** ground (*****, ******, ***** ******). *********** **** ****** ****** **** filters, ***** ** **** ******* ***** ** ******* ** **** were *** ***** ** *** ***** *** ************ ** * given ****.

***** ********* *** ***** ****** **** *** ** *** ***** place ** *** *****, ** *** ***** ****, *** ********* motion ***** ** ******** ** ********* ** ** *** ** object ** ********. ** **** *****, ******* **** ****** ***** or ***** ********* ***** ** **** ** ********* ** ** object *** * ******, ** *******, *** *******. *******, ***** systems ********* *** *** **** * *** **** * ***** or * ********** **** * *******, ** **** *** *** doing **** ******** ** ****** ******* *** ******* ******* **** at ****** ***********.

***** ******* *** **** ***** ** ****************** **** ******* ** not **** *** ***-*** ************, * ****** ******** ** *** ground ******* ****** ******* ******** ***** ** ********** ** * vehicle ******* ** * ******, ***** ***** ****** ***** *** uniform ********:

**** ******** ** ********* *** *********** ******* ***** ** ***-********* static ******** ** ********* ******** ** ** ******* ********.

Machine ******** ** **** ********

******* ******** *** **** ******** *** *******, *** **** ******** different ********** ** * *******. ******* ******** **** ***-********** ************ to ***** * ******** ** ********* ** ***** ** ** object, **** ******** ******* ***** ****** *** *************.

******* ******** *** ** ****** *** ** ********* * ***** walking ** *********** ********** **** ** *** ***** ** *** height ****** ** ****** **** *** *****, ***** ****** ** movement ** **** *** **** **** ** **********, ** ****** move ** * *********** ********* ******* ** ********, ** ****** have **** ***** *** ******* ******* (************ ********), *** ** forth. **** *** ********* ** **** *** *****, ** **** look *** ***** **********, *** ** ** ***** ****** ** them, ** **** ****** *** ***** ******** * ****** *******.

** **** ********, *** ******** ** *** ****, *** **** the **** ********** *********, **** ** * *****. ** **** breaks *** **** **** **** ******* **********, *** ***** *** similarities ****** *** (** ****) ** *** **** **** ** can *** ** ***** ** ************* ** *** ** ********* future ********* ** *** **** *******.

*** **** ******** ********* ****** **** ** **** ******** ** its *** **** ** **** ******* ** **** *** ******* learning ********* *** ******** ********** ****. ** **** *****, *** deep ******** ********* **** ** **** *******, ******** ****** **** humans *** *** **** ******* ** ******** ******, ** **** would **** **** **** **** ********* ** ******** ******, **** as **** *** ******** ************* ** ****** *************** ** ******.

What ***** ** "****"?

**** ******** ***** **** *** ****** **** ******* * ****** of ************ ************** ******, *********** *******, ** ***** *********. * system ******* ** ******** ******** ** ***** ***** **** ******* to ***** ** ****** ******** **** **********, **********, ******** ** badges ** *******, ****** ******, *** **** *****.

**** *** ****** ** ********, **** ****** ***** **** ******* them ******* ******** ****** (*********** ** *** ****** **** ** the ***** *****) ******* *** ******** ** *** ******* ***** various ******* *************, *** ****** * ******** ** ***** ***** of ******* *** **** ****** ** *** *****. ** **** case, "********" *** *** ******* *******, ** ** ******* *** most ********, **** *** ****** ****** ********** *** ***** ******** elements ********** **** "********" *** "*******" ******** ** * ****** extent:

***********, **** * ******** ****** *** ******** *** *** ****** to ** ********** ** "****", ******* ** ** *** ******** for ***** ** ** **+ ****** ** ************** ** **** advanced *******.

*** ** *** ******** **** **** ******** *** ** ***********, the ***** ** *** ******** ******* ** *** * **** indicator ** ******* ****** *********** ** ***********. **** **** *** imager **** ** * ****** ** *** ** ******** *********** factor ** ********** ** ***** *******.

How **** ******** ***** *********

**** ******** *** * ****** ************* ** *** *************** **** define ******* *******, ******* ** ******* ** ************ ** ***** appearance. **** ***** ** ****** **** ** ******** ******* ********** in *********** **********, ** **** *** ****** **** *** ***** any ***** *********** ** ************.

********* ************ ********* ******* ****** ********* ** ****** ** * time ** ***** ***** ** ****** *** ** (*.*.: *********** detection *****-*****). ** **** *****, ********* *** **** ** ****** "abnormal" ********, ****** ******* **** **** ******* ****, ** * large ***** *** ****** ** *** **** ********* ******** (**** as ** * ***** **********). ***** **** **** ***** ****** is ** *** **** ***** *****, ********** ******* **** * blob ** ****** ** * *****, *** *** * *** (or * *****, ** * ****). ** ***** **** ** better ********* ******* ** ******** ** * *****, **** ******** helps ***** ********* ******** ***** ******** *** **********.

The **** ** ********

* **** ****** *******'* *********** ** ***** ** *** ******* and ********* ** ****** **** *** ********. ******* * ****** that *** ******* ** ********* ****** **** ** ******* ** images ** **** ********, ** **********. **** ****** ***** ****** fail ** ********* * ******** ** ******** ******, ******* *** training **** *** *** ****** ******. ** ****, ** ***** perform ***** **** * ******** ********** ****** ******* ******** ******.

*******, **** *** ******** ** ***** ***** **** **** *********, or **** ** ********* ** *************** ** *** ******* ******** for **************. ***** ******** ****** ****** ******* ***** ** *** object **** ******** ******, *** *** ***** **** ******, ** a ******* ** ***** *** ********.

******* * ********** ** ******, *** ******* **** **** * category *** ** **** **** *********.********** *** ******** ********* **** *** *** ********, ** ** contains ******** ** ****** *********** **** ********* ** ********** *** sub-categories. ***"******" ************* ******** ****** *,*** ***-********** ** ******, **** *************** **** "warrior" ** "*********".

***-***** ***** ********* **** *** ********** ** **** **** *****-******* object *************** **** *******-******** *******. *** *******, * *** *** be *** ****** ** ********, ********** ** "**** ********* ******" and "********" (** **** ** ******** ***** *************** **** *****, shotgun, ***.).

**** **** ********, ** ***** ** ********** ** ****** *** system ** ******** ******** ************, ***** ** ***** ***************, ********* impractical *** *******-******** *******.

*********, ** ***** ***** * ****** ***** ****** ** *** and *****, ***** *** ***, ** ***** * *** ******* of *********** ****** *** ***. ********* ** **** **** *** becoming ******* ** ****** ************ ** ***** ********* ** ******* customer ******** ** ****** *** **** ** **** ************** ** browse ********.

Gender *** ***

*** ******* ***********, ********* ** ************ *****, *** ** ****** applications ** ** ****** ******** *********** ***** ** ***** ****** and ***. **** *** **** ******** ****, ****** ****** ** men *** *****, *** *** *****, **** ****** *** ******** to ****** ***** *********** **** ** ****** ** **** **** have **** ******* **. ******** ***** *******:

Filtering ****** **** **** ********

*** ********* **** ** ******* ****** ***** ************ ** ***** deep ******** ** * '******'. *** ******* ** **** ******** every ***** **** * ************ ****** ***** ** **** ******** intensive. ******* ** ***** ****, *** ****** ***** *** *********** video ********* ***** ** ****** **** *** ********* ******* ** analyze, **** ********** **** ****** ****** ******* ** **** ******** to ****** ** *** ****** ******* ** ********, *** *******, a ******, ******* ** * ***, * *********, * ****** or * *****. *** *******, ******* ********* **** ******** ******** ****, ** ***** **** ******* **** *********:

Training **** *** *********

**** * ********* ***********, ***** ** ** *** *** * user ** **** *** *** ****** *** *******, ************* ********* will *** ******* ******** **** *** ********. ***** ***** *** data **** ** ******** ** ********** ** *** ************ *** adapted *** ***-***** ** ***** *******, ********* ********* **** **** would **** ***** ************* ** ********* ** ***** **** ** re-use *** **** **** *** ***** *** ******** ********.

Potential ******** ****** *******

**** ** ******* ** ******** **** *** ** *********** **** systems *** ******* ***** ** ****-***** ******* **** *** ***** to *** ********** ******, *** ****** **** ***** *** ******* will ** ********. ******** *** **** **** ********* ** ***** vs. ****** ** ** * ******** ****** **. ** ********** area, *** ***** **** *** *** *** ****** ** *********** in ***** ****** ***** **** * ****** ** ******. ********, a ****** ***** ** ******* **** ********* ***** ** ******** or ******* ********. **** * ****** ******** ** ******* **** people ** ********* ********, ******, ***. ***** **** ******.

Hardware ************

**** ******** ******** ******** ********* *** *** *********** ********:

  • ******** *** ****** ******* **** ******
  • ********* *** ****** ******* ** * ******* **** * ****** or ********

**** ** ***** ******** **** ** *** *** ** ****, this ** ************ ********* ** *** **** ** *******/*********, ** they **** *** **** ************* ***** **** ****, ******* **** new ******** ** ********* ******** *** *** ********* *** ******** to **** **** **** * ******** *******.

******** ** **** *************** *********, *** ********* **** *********** **** designed *** **** **** **** *** **** **** ********, *** expensive, **** **** ** **** ** * ****** ** ********. Depending ** *** ****** *** ********** ** ****** **** *** training, **** ******* *** **** *****, **** ** ***** ** complete, *** ******* **** ** ******** **** ** ********. *** training ***** ******* * ***** **** *** *** *** ** use ** ******** *******, **** ***** ** ********* **** ***** relative ** *** **** ** *** ***** ****. ****** ** a ****** ******** ** **** *** **** ****-*********** ******** *****.

********* *** *** ** * ****** ** ******** **** * lower-power *** ** **** **** **** ******** ** **** *******. Here, *****-**** *** ** **** ******* **** *** ***** ***********, and *** ****** ** ******* **** *** ** ******** *** classified ** *** *****, ** *** **** ** ***** *** system ** ******** ** ******. ********* *********/********, ************** ******* *********** **** ******** *** ****-***** ************.********** *** ****-***** ********, *** **** ******** ***** ********* ***** designed *** **-***** ********.

Deep ******** ** ************ ********

******* ** **** ******** ***** ************ ******************* ********* ** *** ******** ******** ******** ******** **** **** level ** **** ******** ******** ** ************. ************ ***** **** facial *********** ** *********** ****** *******, ** *********** ****** ****** to ****** ******-**** ****** ************.

Evaluating **** ******** ********

** *** *** ********* ** ****** * **** ******** *******, IPVM ***** ******** ********* *** ******* ** ****** ** * location *** *********** ** ******* ** *** ******** ********** ** possible. ***** ************ ***** ***** **** ****-**** *********** *********, **** do *** ****** *** ****** ************ *** ****-***** ***********. *******, tests ***** ** ********* **** * ****** ** *-* *****, giving *** ****** ********** **** ** *** * ******* ** objects, ******** *********** ** ** ******** **** ***/***** ********** *** across * ****** **** *** **** * ***** *****-**** ******* lot ****.

Future ********* *** **** ********

********** ********, *** ***** ** *** ** *** **** ******** development ** ********** ** *** ***** **** ** ** ******* and ******** *****. *** ************ ********* ***** *** * ******* improvement, ** **** *****, **** ******** *******, *** *** ***** far **** *****. ************ *** ***** ***** **** ** ****, core ********, *** **** **** **** **** *** ******** **** we ********** *** ******** ********* ***** ** **** ****** ***** when ******** ** ***** *********** ** *** **** *-** *****.

***** **** ** ********* **** *** ***** ********* **** *** be ********* **** * **** ******** ******* *** ******* **** deploying * *********-********* ********. *******, ***** **** * **** ********* need, ************ ** ******** ***** **** ****** *** ******* *********, would ** **** ** ******** ******* ** ****** * ******** too ***** ** *** ********* ***** ** **** ********.

Comments (26)

******** ** ****** ******, **** ******** **** **** ****** * bigger *** ****** ****** ** ** *** ** ********* ****** in *** *********. ******* **** ** **** ** ******* ******** lines *** **** ***** **** ** ***** ******. ******* ********** can ******* ** **** **** ** ****-******* ****.

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

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

*** **** * ***** **** **** ******* ** *** *******. From *** *******:

******* ******** **** ***-********** ************ ** ***** * ******** ** recognize ** ***** ** ** ******, **** ******** ******* ***** things *** *************.

**** ** ** ****** **** *** ******** ** ******* ********. From *********:

******* ******** ** * ***** ** ******** ******* **** ***** computers *** ******* ** ***** ******* ***** ********** **********.

********* ** ** *************, **** ******** ** **** * ******* case ** ******* ********, *** ** **** ********** **** ***** automatically ** ********** ******** ****. *** ************** ************* * **** ** ******* ******** **** **** ******** **** of ******** ****, *** ***'* ********** **** ********. * **** used **** ********** *** ********* ******* ****** ** * *****, both ******* ********* ** ****** ** ******* ******.

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

********** ******* ** **/******* ********/**** ********** **** ********-****** *******. **** *** *** ********* ******* ** show ***** ******* ******** ******** ****** ******** ***** ******** **** "hand ******" ** ***** ** **** *** ******** ******* **** effective. **** **** ****** ** *********** ******* ****** ******* **** in *** *** ** ************* *** ******** ** *** ****** overall *******.

** ** ****** ***, *** ** *** **** **** *********** areas *** ******* ******** *** **** ***** *********** ******, ****** ** ***** ******** * ***** **** ** ****-****** to *** *** *** ****.People ***** ** ** *** ***** ****-***** *********** **** **** ********* ******* ** *** ******* ***** ******** ***** ** ****** ******* *** *******; ***** ********* ** ********* ** ** *** ***** *****; * ********** ** ********* *** ******* “*-*-*-*.” From all those hand-coded classifiers they would develop algorithms to make sense of the image and “learn” to determine whether it was a stop sign. [Emphasis IPVM]

**** ** ******* ** ** ******* ** *** ****** ** giving *** ******* ******** ****** **** ****** ********** ** ****** that ** *** *** ** ********* **** ******* ** *** scene ****** ** ******* ********.

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

******* ********** *** **** ***** ** *** ******** ** ***** ********** to ***** ****, ***** **** **, *** **** **** * determination ** ********** ***** ********* ** *** *****. ** ****** than ****-****** ******** ******** **** * ******** *** ** ************ to ********** * ********** ****, *** ******* ** “*******” ***** large ******* ** **** *** ********** **** **** ** *** ability ** ***** *** ** ******* *** ****.

* ********* *** ********* *** ****** ******** ***********. * ** not *** ** ** * ********** ** ******* ********. * see ** ** ** ******* ***** ******* ******** **** ***** you ** ***, *** **** ** **** ***** ******** **** coded ************ ** ******* *** ********. ** **** **** * definition ** ******* ********, **** ** ***** ** ********* ***** methods ** ********* ********, **** ** *** **** ******* ********* that ** *** ********, *** *******.

** ***** * ******** ****** ******* *** *** ** ****** a ************ ***** ** *** ********** ** ** ********. *** example, ** ********* ******* ****** ** **** ** ****** ************** what * ******* ***** ***** ****. *** **** ********** ******* machine ******** ** ********* ******** ****** *** ********** ****** ******** is **** ** ********* ******** ****** **** ***** **** ** explicitly ******* ** * ********** *** **** ** *** ** refined ** ******* ******** (*** *******, *** **** ******** ********** may ** ***** ************* *** ******* ********). ** ********** ****** networks *** ***** ** ******* ********** *** * ******** *** (and ** ******* ** **** ***'* **** **** ******** *** network *** ******* ** ***** *** ****).

** *** *** ********* ** ****** * **** ******** *******, IPVM ***** ******** ********* *** ******* ** ****** ** * location *** *********** ** ******* ** *** ******** ********** ** possible.

**** ** * **** **** ******. ******* ** ** ** not ******* **** ***** ******** *** **** ** * ******* then **'* ********** ** ******* ** ***** ********** *** ******* will **** ****** ****. *** ** ***** **** *** ******* will **** ** ********** ******** ** **** **** ***** ****.

**** ***** **** ** ********** ******* ** * ********** *** then ** *** ** ******* ** ******* ********

***, *** * ***** ***** **** **** ***** *** ** very ******* **** **** ** ********, ** ******** ********** ** not **** ** ****** ************** **** * ******* ***** ***** like. *****, * **** *** ******* ** ******* ******* **********. Feed ** **** ***** ** ******* ****** ** ** **** as ******** ****, *** ** **** ***** **** ** ***** effort **** ** ** ****** ******* ****** ** * *****.

*** *** *****. * ***** *** ** **** ** **** general. *** **** ******* *** ********** ******** *** ******** **** other. * **** ****** ** ********* **** ***** ****** ******** we *** ** **** **** *** **** ***** **** * researcher ** * ********. *** *******, ** ******* ********** *** basic ******** **** *** ****** **** *** (******) ******* ** a **********. ** ************* ****** ******** **** ***** ******** *** calculated ****** ******** *******. ** ****** ***** *** ***** * lot ** **** *** * ********** **** **** ****** ******** :)

***, ******. *** ** ** *** **** * ** *********** with ***** ** *** *********** ******* **** ******** *** **** traditional *******. ***** * ******** ** *** *** ******* ***** to ****** *** *********** ************ ** **** ***** *********** ******* *** ******** *** ****** including **** ********. **** ** **** *** *******, ** **** industry ** *** *****.

* ***** ** ** ********* ** *** *** *********** *****. For *******, * ******* ****** ** ******** ** *** *** term******* ********** ***** ********* ********* ******* ** ***** ********* ** *** article ** **** ********* **** **** ** **.

* ******* ****** ** ******** ** *** *** *********** ********** ***** ********* ********* ******* ** ***** ********* ** *** article ** **** ********* **** **** ** **.

**** ** *****, **** **** *************, **** ******* ********** ***** ******* ** ***** "******* ********" but *****'* ******* *** **** **** ********

...**** ******** ******** ****** *** ******* ******** **** *** **** a ...

*** ****'** ** ****** *** **** ******** ** ***** *******.

*****, ********* *******! * ***** **** **** *****: ******* ******** implies "********." *** ******** ***'** ***** ** **** ***** ** analytics ** **** * ***** **** "***** *****," ******* ***** is ** ********. ***-******* ****** ***** *** ****** ******* ** images ** *****. ****** ***** ** * ***-**-***-**** ********** ***** hits ** ********** ******* ****, *** **** ******** **** ** used ** ****** ** ****** *** ******** *****, * ***'* see *** "******* ********" *** ** ** ******** **********.

*******, ***** *** *** *** ************ ******** *** *** ** "artificial ************."

******* ********, ***** ******, ******* ** ** "******" ** ****-****** some ***** *********** ** * ******** ** *** *******, ** as **** ****** **** *** ******* ***** *******.

** ***'*, *** **** *** ****** * ****** ** ******, essentially ******* ** **** **** **** *** **** ** ****** ("these *** ******** ** ******"), ** **** ****** *** ************* and *********** ********** ** *** ***, ******* ****** ** ***-****** anything.

******* ********, ***** ******, ******* ** ** "******" ** ****-****** some ***** *********** ** * ******** ** *** *******

*** ** ********, *** ****** ** *****. *** ********** ** machine ******** ** ******* **** ****, *** *** ********* *** limitations ** **** *********** ******* ******** ********** **** *** ***** definition ** ******* ******** *** ** ***** ** *** ********* some ******* ******** ******* **** ******* ** **** **** ****** of ***********. ** ***** ** **** ******** ** *** **** "traditional ******* ******** ********** ****** **** ********", ****** **** "******* learning ****** **** ********".

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

* ***** *** **** *** ************ ***** **** ** ** referring ** ** *** *********** *** ******* ** *** ******** developers *** *** ******** ** *** ******, *** * ******* mathematical ***** ******* ** *** ***********/********* ** *** ********** *** built **** *** ********* ******. ***** ****** *** ** ******* enough ** ****** ******* ******, ** ****, ** ***** ********* only ** *** ******** ****. *****, * **** ** *********** with *** ****** ******* **********, * *** ** ** **** quite ****** **** *** *** ** **** ***** *********** ** mathematical ***** *** ********.

***** *** ******** ******** ********* ******* ******** ** **** ********, where *** ******* ******** ****** ** ***** **** ****-***** ********** to **** ***, *** **** **** **** *********** ** ********** for *** ******** ******* ** ***** *** *********** ** *******.

**** ** *** *******:**** ******** **. ******* ******** – *** ********* *********** *** need ** ****!************ **** ****** ** ******* ** * ******* ******** ****** designed ** ****** ******* ** ******:

** ** ***** **** ** * ******* ******* ******** *******, we **** ****** ******** **** ** ** *** ****** *** whiskers ** ***, ** *** ****** *** **** & ** yes, **** ** **** *** *******. ** *****, ** **** define *** ****** ******** *** *** *** ****** ******** ***** features *** **** ********* ** *********** * ********** ******.

***, **** ******** ***** **** *** **** *****. **** ******** automatically ***** *** *** ******** ***** *** ********* *** **************, where ** ******* ******** ** *** ** ******** **** *** features.

**** ** ******* *******:

** ****’* *** ********** ******* ******* ******** *** **** ******** then? **** ******** ******************** ********, *** ***** * ******** ******* ******** ***** ***** need ** ** **** *** ** ****** **** ** ******** prediction (** ******* ** **** ****), * **** ******** ***** is **** ** ***** **** ** *** ***.

*** *******:

*** ********* **** **** ******** *** **** *********** ***** ** machine ******** ** **** ***** *** ****** **** ** ******* a ********** *** ** ******** ** ***** **** **** ***** predictions, **** ******** *** ******** *** ********** ******** ******.

*** *******, ** * ****** ****** ** ******** ***** ***** in * ***** ** ***** *** **** ** ** ***** be *** *** ********** ********, **** ** ***** *** ********. It ***** ******* ** *** ** ****** ***** **** ** can **** ** ********** *** ********* ******** ** ***** ** make ** *********** ********** ***** *** ******* ** *** ******.

*** *** ******* ** **** ******, ***** ** ***** *********/******* vision, ******* ******** ******* **** ***** **** *** ******* **** amount ** ****-****** ** ********** **** *** ****** **** ** determine **** ***-******* ** *** ***** ** ****** ******* *** learn ****. **** **** ** **** ****-******, **** ** *** need ** ** **** **** ****** **** ** **** ******** aspect ******, ** ******** ********** **** (** * **** ********** example).

**** **** ******* ******, ***** *** ********** ** ****, *** we ***** ***** **** **-***** ******* ** ***** **********, ***., but ** ***** ** ****** *** ***** ** * '********', and ******** **** *********** ** *********** *** **********.

*****, *** *** ***** ** **** * **** **** **** all ****. *** **** **** **** **** ********** ** **** it ******** *** ********'* ***** *************, *** ***** **********, ********* some *** ************. ****** * ****** **** *********** ****** ** a **, ******* ** "**** ********" *** ********* ** ** the **** ******** ***** ** ****** *** **** **********. ** seems **** ***** ***** ****** ** *** & **** ** touting **** ********, ** **, *** ******* *** **** ** exactly **** **** *** ***** *** **** *********** *** **** it ****** *****. *'* **********, *** ********** **.

** ******** ***** ** **** ** ** ********** ******** ****** **** ********, ** **** ******** ** * **** ** ******* ********, rather ** ****** ****** ******** ************************ *********** **** *** *********** *** ******** (********* **** ***** **********) are *** ******** ** *** ********** ** ******* ********. *** titles ** ***** ******** *** **** ****** ** *** *********.

**** **********, ***, ** *** *** ******** ** ****** *** system ***** ** *********** ******* ******** **********, *** **** ********** have **** ****** ** *** ******** *** **** ******* ***** that *** **** ** ***** **** *** (*.* *******, *** bars *** ***** ***** ********* *******, ********* ***** ********** ***) whereas *** **** ******** ******** ***** ** ***** ********** ** well **** *** *** ******* ***** ******* ****** **** **** a ****** *****. *** **** ** **** ****** ****.

"*******, ***** *** *** *** ************ ******** *** *** ** 'artificial ************.'"

*****... *** ****'* ******* **** ************** ** ***** **** ******** ******* *****...

**** **** ******* *.*. ****, ** *** ********* *** ***** mentioning **** ******** *****. **** ********** ** ** * ******* of ********** ************, ***** ** *** *****.

"**** **** ******* *.*. ****, ** *** *********..."

*** - '*****'.

** ******* *** ******* *** ** ***** ****** ** ***** thanking *** *********** *** ****. *** ******* ********* ***** **** ******** ********- ***** *** **** * *** **********.

********** ** ******* * *****. * ***** **** *** ***** frames/opening ** *** ***** *** "****":

"****'* ******* **** ************** ** ***** **** ******** ******* *****..."

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

** ** ******* * **** ******** ***** ** *** *** first ****** - ***** ** *********** ******** ** *** ********** Intelligence ****** (***** ***** ** ****** *** * **** ****).

*.*. ***** '**** ********' ******* ***** '*****' **** *** **** jokingly ********* ** ****.

**** ** *** ** ******* ** ** ********* ****, *******, it ** ****** **** **.

**** ****** ***** *********** ** ** **** ** *** ********, it's ** ******* *** ** ********** **** *** **** ****** against ***** *** ********** (** ****** * ********** ****** ** agreement). ** ***** ******* ********** *** ******* ** * ******, and ****** ******* ***** ******* *** ******** ** ************, ***** is ** ********. ******* ********, ** *** **** ** ********, needs ** **** * ******** (****** ******** ** ********) ** induce *** ********.

**** ** ***** * *** *** ** ********** *** ********** between *** *** ***'* **** ******** ** ***'*

*****://*****.**/-**********

** *** **** ***** ** ************** **** ********** ** *****, but ** *** ********** ** ***** **** ** **** *** concept ***** *** ** ******* *** **** ******* ** *** very **** ******.

**** ** * **** ****** ******** ** ******* ******* **** of *** ******* ******** ** ******* ********, **** ********, *** AI. ** ******** ******** *** ******* ************ ****** **** ****** called ******* ** ** **'* **** ********** ** ***** **** about *** ********* ** **** **** *** *******.

Login to read this IPVM report.
Why do I need to log in?
IPVM conducts unique testing and research funded by member's payments enabling us to offer the most independent, accurate and in-depth information.

Related Reports

Avigilon Announces AI-Powered H5 Camera Development on Sep 19, 2018
Avigilon will be showcasing "next-generation AI" at next week's ASIS GSX. In an atypical move, the company is not actually releasing these...
Amazon Ring Spotlight Cam Tested on Sep 17, 2018
Amazon's Ring has released their latest camera entry, the Spotlight Cam, which we bought and tested in our Consumer IP Camera Analytics...
IP Camera Cable Labeling Guide on Sep 14, 2018
Labeling cables can save a lot of money and headaches. While it is easy to overlook, taking time to label runs during installation significantly...
VMS Export Shootout - Avigilon, Dahua, Exacq, Genetec, Hikvision, Milestone on Sep 13, 2018
When crimes, accidents or problems occur, exporting video from one's video surveillance system is critical to proving incidents. But who does it...
US DARPA Investing $2 Billion In AI on Sep 11, 2018
The US Defense Advanced Research Projects Agency (DARPA) is granting more than $2 Billion to companies developing new AI technologies. The money...
Drain Wire For Access Control Reader Tutorial on Sep 04, 2018
An easy-to-miss cabling specification plays a key role in access control, yet it is commonly ignored. The drain wire offers protection for readers...
Exit Devices For Access Control Tutorial on Aug 28, 2018
Exit Devices, also called 'Panic Bars' or 'Crash Bars' are required by safety codes the world over, and become integral parts of electronic access...
Inputs/Outputs For Video Surveillance Guide on Aug 24, 2018
While many cameras have Input/Output (I/O) ports, few are actually used and most designers do not even consider them. However, a good understanding...
Backup Power for Large Security Systems Tutorial on Aug 24, 2018
Choosing the right backup power system depends on system size. While small and medium systems greatly benefit from using UPS battery backup...
Luxriot VMS Profile on Aug 23, 2018
Luxriot is more popular than Hikvision and Milestone products according to ASMAG which was probably even surprising to Luxriot. The company has...

Most Recent Industry Reports

Avigilon Announces AI-Powered H5 Camera Development on Sep 19, 2018
Avigilon will be showcasing "next-generation AI" at next week's ASIS GSX. In an atypical move, the company is not actually releasing these...
Favorite Request-to-Exit (RTE) Manufacturers 2018 on Sep 19, 2018
Request To Exit devices like motion sensors and lock releasing push-buttons are a part of almost every access install, but who makes the equipment...
25% China Tariffs Finalized For 2019, 10% Start Now, Includes Select Video Surveillance on Sep 18, 2018
A surprise move: In July, when the most recent tariff round was first announced, the tariffs were only scheduled for 10%. However, now, the US...
Central Stations Face Off Against NFPA On Fire Monitoring on Sep 18, 2018
Central stations are facing off against the NFPA over what they call anti-competitive language in NFPA 72, the standard that covers fire alarms....
Chinese Government Praises Hikvision Following Xi Jinping on Sep 17, 2018
The Chinese government council responsible for managing China's state-owned companies praised Hikvision’s obedience to China’s authoritarian leader...
Amazon Ring Spotlight Cam Tested on Sep 17, 2018
Amazon's Ring has released their latest camera entry, the Spotlight Cam, which we bought and tested in our Consumer IP Camera Analytics...
European Mega Security Firm Verisure Pushing Security Fog on Sep 17, 2018
The European mega security firm Verisure (Securitas Direct), with a reported 2 million customers, is pushing security fog, as shown in this BBC...
IP Camera Cable Labeling Guide on Sep 14, 2018
Labeling cables can save a lot of money and headaches. While it is easy to overlook, taking time to label runs during installation significantly...
Favorite Intercom Manufacturers 2018 on Sep 14, 2018
Intercoms are certainly increasing in popularity, driven by the integration of video and IP networking. But who is the favorite? On the one side,...

The world's leading video surveillance information source, IPVM provides the best reporting, testing and training for 10,000+ members globally. Dedicated to independent and objective information, we uniquely refuse any and all advertisements, sponsorship and consulting from manufacturers.

About | FAQ | Contact