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

Directory of 30+ LPR / ANPR Providers on Feb 21, 2018
License Plate Recognition / Automatic Number Plate Recognition are a type of video analytics software that can identify and match license / number...
Remote Network Access for Video Surveillance Guide on Feb 21, 2018
Remotely accessing surveillance systems is key in 2018, with more and more users relying on mobile apps as their main way of operating the system....
Hikvision DeepInMind Tested Terribly on Feb 15, 2018
While Hikvision is heavily marketing deep learning and 'AI' as their next big thing, new IPVM test results of their DeepInMind NVR shows their deep...
Assa's Lowest Power Draw Maglock: Securitron M680E Examined on Feb 14, 2018
Securitron produces some of the most extreme maglocks on the market, including massively strong maglocks and even ones with integrated CCTV cams...
Motorola Targets Chinese With Avigilon Acquisition on Feb 09, 2018
Motorola joins the growing list of companies taking aim at Chinese manufacturers. Recall, last week it was Hanwha: Chinese Products Damaged...
Arlo, Bigger Than Avigilon, More Valuable Than Axis on Feb 08, 2018
Arlo, the wireless IP camera offering that Netgear bought ~5 years ago for a few tens of millions is now doing more revenue than Avigilon and...
PoE Powered Access Control Tutorial on Jan 19, 2018
Powering access control with Power over Ethernet is becoming increasingly common.  However, access requires more power than cameras, and the...
CES 2018 Show Final Report on Jan 12, 2018
This is IPVM's final edition of our 2018 CES show report. Below are already numerous images and commentary, with more coming tomorrow.   CES is...
The Interceptor Aims To Fix Vulnerability In Millions of Alarm Systems on Jan 08, 2018
Security executive Jeffery Zwirn claims a 'catastrophic' flaw exists in 'millions of alarm systems', and dealers could be liable if not fixed. The...
Multicasting Surveillance Tutorial on Jan 04, 2018
Network bandwidth can be a concern for some surveillance systems. While improvements in video codecs, such as smart codecs for H.264 and H.265,...

Most Recent Industry Reports

False Advertising: Hikvision USA Deep Learning on Feb 23, 2018
Hikvision USA is conducting a false advertising marketing campaign for their deep learning system. Hikvision USA's claim violates US FTC Truth In...
Favorite Integrator Sales Quote Software (Statistics) on Feb 23, 2018
What application do integrators use the most to issue sales quotes? Nothing? Spreadsheet? MS Project? Online software? Of the many offerings out...
Aruba Networks Profile on Feb 22, 2018
Aruba Networks' presence in the video surveillance market has historically been limited. With a company focus on Wi-Fi first and switching...
US Army Base Specifies 70+ Outdated Hikvision Cameras on Feb 22, 2018
A US Army base has specified 70+ Hikvision IP cameras, a month after the WSJ reported a different Army base removed Hikvision IP cameras. While...
Directory of 30+ LPR / ANPR Providers on Feb 21, 2018
License Plate Recognition / Automatic Number Plate Recognition are a type of video analytics software that can identify and match license / number...
New Whole Foods Installs Hackable Access Control on Feb 21, 2018
Whole Foods has built a reputation for high quality. And their 2017 Amazon acquisition has increased that, plus added deep pockets for buying...
Remote Network Access for Video Surveillance Guide on Feb 21, 2018
Remotely accessing surveillance systems is key in 2018, with more and more users relying on mobile apps as their main way of operating the system....
Visio For Video Surveillance Design on Feb 20, 2018
Many integrators have standardized on AutoCAD for camera layouts but new users may be overwhelmed by its learning curve. Microsoft's Visio...
Health Care Insurance Integrator Benefits Statistics on Feb 20, 2018
How common and how much healthcare coverage is typically provided by security companies? 150+ integrators explained how their companies provide the...
Hikvision Deletes Genetec Support on Feb 20, 2018
There will be no peace between Hikvision and Genetec. A year after Genetec expelled Hikvision (and Huawei, citing Chinese government control...

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