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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Axis Releases First New Access Controller In 5 Years (A1601) on Jun 15, 2018
It has been 5 years since Axis 2013 entry in the physical access control market, with the A1001 (IPVM test). Now, Axis has released its second...
ReconaSense - The AI / Access Control / Analytics / IoT / Video Company Profile on Jun 12, 2018
One company's ISC West booth stood out for displaying a light-up tower of buzzwords. The company, ReconaSense, pledged to be 'making sense of it...
Introducing Effective PPF (ePPF) - Improving Video Surveillance Designs on Jun 11, 2018
Pixel density (PPF / PPM) is the best metric the industry has to define and project video quality. It allows simple communication of estimated...
Powerline Networking For Video Surveillance Advocated By Comtrend on Jun 08, 2018
Powerline networking, using existing electrical wiring, has been around for many years. Indeed, over the years, some video surveillance providers...
H.265 / HEVC Codec Tutorial on Jun 07, 2018
H.265 support has improved significantly in 2018, with H.265 camera/VMS compatibility increased compared to only a year ago, and more manufacturers...
Bosch IVA Video Analytics And Motion+ VMD Tested on Jun 06, 2018
Bosch's video analytics now ship on nearly every model, from indoor domes to high-end 5MP starlight cameras.  In this test, we evaluate Bosch's...
Princeton Identity Access 200 Iris Scanners Examined on Jun 05, 2018
Iris recently registered a big jump as a preferred biometric in our Favorite Biometrics survey, but access-ready options can be difficult to...
Keypads For Access Control Tutorial on May 31, 2018
Keypad readers present huge risks to even the best access systems. If deployed improperly, keypads let people through locked doors almost as if...
Hanwha Wisenet X Analytics and VMD Test on May 24, 2018
Continuing our updated testing of camera analytics, we tested Hanwha's Wisenet X analytics for over two weeks in multiple scenes, indoors and out,...
Installing Box Cameras Indoors Tutorial on May 22, 2018
This tutorial starts our physical installation for video surveillance series, starting with Box Cameras, one of the oldest and most basic types....

Most Recent Industry Reports

IFSEC Show Report - Live From London on Jun 19, 2018
IPVM is live from London reporting on the IFSEC show. The Chinese have taken over the UK, centered on Hikvision, flanked by Dahua, Huawei and a...
Axis Guardian - Cloud VMS for Alarm Companies on Jun 19, 2018
Axis has struggled to deliver a cloud-based managed service video platform. Video service providers have utilized AVHS for over a decade, and have...
IPVM Vulnerability Scanner Released on Jun 18, 2018
IPVM is proud to announce video surveillance's first and only cybersecurity vulnerability scanner. This tool allows quickly and simply...
Hikvision Corrects False Cybersecurity Announcement on Jun 18, 2018
Hikvision has corrected a false cybersecurity announcement that claimed a British government-sponsored program endorsed the cybersecurity of...
July 2018 IP Networking Course on Jun 16, 2018
The last chance to save $50 on registration is this Thursday, June 21st. Register now and save. This is the only networking course designed...
The Dumb Ones: PSA's Bozeman On Cybersecurity on Jun 15, 2018
The smart ones are the hundred people who flew to Denver and spent $500+ on a 1.5-day conference featuring Dahua as a 'cyber responsible partner',...
Amazon Ring Launches $10 Monthly Professional Alarm Monitoring on Jun 15, 2018
Amazon's Ring has announced an alarm system with 24/7 professional alarm monitoring for $10 per month, a fraction of the $30+ per month traditional...
Axis Releases First New Access Controller In 5 Years (A1601) on Jun 15, 2018
It has been 5 years since Axis 2013 entry in the physical access control market, with the A1001 (IPVM test). Now, Axis has released its second...
Hikvision 12MP Fisheye Camera Tested (DS-2CD63C2F-IV) on Jun 14, 2018
Hikvision's DS-2CD63C2F-IV is their flagship panoramic camera, with a 12MP imager, 15m integrated IR, smart codec, and more. We tested the 63C2 in...
Four Major Outdoor Camera Install Problems on Jun 14, 2018
Over 140 integrators told us the top four camera installation mistakes that lead to unexpected problems and failures. Their comments often...

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