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

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Directory of Video Intercoms on Nov 13, 2018
Video Intercoms, also known as Video Door-Phones or Video Entry Systems, have been growing in the past decade as more and more IP camera...
Beware Amazon Go Store Hype (Tested) on Nov 13, 2018
IPVM's trip to and testing of Amazon Go's San Francisco store shows a number of significant operational and economic issues that undermine the...
Genetec Privacy Protector Tested on Nov 12, 2018
Genetec has built Kiwi Security's Privacy Protector into Security Center, an analytic which anonymizes individuals in cameras' fields of view...
Axis 2N Intercom Tested on Nov 08, 2018
Axis expanded its video intercom business buying Czech-based 2N in 2016. Despite competing against owner Axis' intercoms, 2N recently registered as...
Ubiquiti Protect Video Surveillance Profile on Nov 07, 2018
Ubiquiti has now been in the video surveillance market for 7 years (see our first coverage back in 2011). In that time, the company's revenue has...
Kogniz Silicon Valley AI Startup Profile on Nov 07, 2018
Kogniz is a Silicon Valley company that aims to bring AI analytics to security and surveillance, centering on their own smart cameras: We spoke...
Directory Of Video Doorbells on Nov 06, 2018
Video doorbells are one of the fastest growing categories in video surveillance, especially among residences. The optimal placement of these...
Avigilon Opens Up Analytics And Cameras on Nov 06, 2018
Avigilon is opening up. The company historically famous for advocating its own end-to-end solutions and making it harder for 3rd parties to...
Solar-Powered, Smart-Phone-Based Access Kit (VIZPin) Examined on Nov 02, 2018
Cloud-based access control company VIZPin is releasing a solar-powered and smart phone based access control system for gates and other remote...
Video Surveillance Hard Drive Failure Statistics 2018 on Nov 02, 2018
Hard drive failures can be significant service problems but how common of an issue are they in video surveillance? How long do drives last when...

Most Recent Industry Reports

Throughtek P2P/Cloud Solution Profile on Nov 15, 2018
Many IoT manufacturers either do not have the capabilities or the interest to develop their own cloud management software for their devices....
ASIS Offering Custom Research For Manufacturers on Nov 15, 2018
Manufacturers often want to know what industry people think about trends and, in particular, the segments and product they offer.  ASIS and its...
ISC East 2018 Mini-Show Report on Nov 15, 2018
ISC East, by its own admission, is not a national or international show, billed as the "Largest Annual Northeast U.S. Security...
Hikvision Silent on "Bad Architectural Practices" Cybersecurity Report on Nov 14, 2018
A 'significant vulnerability was found in Hikvision cameras' by VDOO, a startup cybersecurity specialist. Hikvision has fixed the specific...
French Government Threatens School with $1.7M Fine For “Excessive Video Surveillance” on Nov 14, 2018
The French government has notified a high-profile Paris coding academy that it risks a fine of up to 1.5 million euros (about $1.7m) if it...
Integrator Credit Card Alternative Divvy on Nov 13, 2018
Most security integrators are small businesses but large enough that they have various employees that need to be able to expense various charges as...
Directory of Video Intercoms on Nov 13, 2018
Video Intercoms, also known as Video Door-Phones or Video Entry Systems, have been growing in the past decade as more and more IP camera...
Beware Amazon Go Store Hype (Tested) on Nov 13, 2018
IPVM's trip to and testing of Amazon Go's San Francisco store shows a number of significant operational and economic issues that undermine the...
Magos Radar Company Profile on Nov 12, 2018
Magos America General Manager Yaron Zussman admits when he first came across Magos, he asked himself: "What's innovative about radar?" Be that as...
Genetec Privacy Protector Tested on Nov 12, 2018
Genetec has built Kiwi Security's Privacy Protector into Security Center, an analytic which anonymizes individuals in cameras' fields of view...

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