********* ******** *** $* ******* in ******* ** ****, ****** **$** ******* ** *******.

*** **** ***** *********** live ** ** *** hype **** **** *****?

** ***************'* ****** ******** *****************:

• *** **** ** ******* in **** ***** ************ scenarios?
• **** ** ***** ******** a ****** ** * different ******?
• **** ** **** ***** walking ******* *** *****?
• *** ** ***** ********* faces ** ****** ******* sunglasses, ****, *******?
• *** **** ** ******* at ***** ** *** light (~* ***) ** dark/IR (~*.** ***)?
• **** ** ****** ******** other **** ***** *****?
• ** *** **** ********* easy ** ********?
• **** ** ********* **** major *** *******?

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

*******

*********'* ******** ** ***** to ** **********, ********* as **** ***** ** possible ** *** ***** of ****. ** **** 30 **** ** *******, this ******** ****** ** have **** *********, **** reliable *********** ** ***** PPFs, ********* ******** *****, and ** ******* ******, with *** ***** ************.

*******, ** ******* **** a ***** ****** ** false ********** ** ********* objects **** ** ******, puddles, *****, ***., (****** these ******* **** *** recognized ** ********). ************, it ************* *********.

********, ********** ** ********* had *********** ********* ********, both **** *********'* *** Windows/Linux ******* ** **** as *********** ****** **** third ***** *****, ********* out-of-date ******** *** ***********.

Detailed ********* / *********** ********

***** ** *** *****, Anyvision's ****** ******** ****** recognition *** ******* *********:

• *********** ** ***** **** than ******:** *** *****, ********* was **** ** ********** recognize ******** ** ~**-** PPF ** **** *** scenes, ***** ***** ******* than **** ***** *********, generally ********* *** *** or ****.
• *** ***** ***************:****** **** **** * month ** *******, ********* incorrectly ********** ******** times ****** *** *******, using ***** ******* ********** threshold ** *.**, **** a **** ******** ** large ** ***, **** more **** *** ******** passing ** ***** ** these *******. *******, **** is * ***** ********** compared ** **** ************* in ******
• *********** ** ********* ****** solid ** **** *** scenes:*********** ** **** *** scenes *** **** ********, able ** ******* ******** with **** ********** ****** (0.65+) **** **** **** vertical ******** >**° ***/** horizontal ***** ** ********* of ** ** **°, greater **** ***** ****** recognition ********* ** **** tested, ***** *********** ******** with **** ****** ********.
• *********** ******** **** *******, hats, ** *****:****** *********** **** ** hats, **********, ** ******* reduced *********** ********** (** 0.03-0.07) *** ***** ******** recognition ** **** *** scenes, **** **** *********** downtilt. *****, *******, *** other **** ********* *********** stopped ********* *** *********** altogether.

******** ********* *** *********** had *** ********* ******:

• **** ****** ** ********** of ***-***** *******:** *** *****, ********* detected ***-***** ******* ** faces *********, **** ** wheels, *********, *******, *** other *****, ********* ********* hundreds ** ***** *** day. ***** ********** **** never ********** ** ****** and ******** ******* *** be ******* ** *** UI, *** ***** *** still **** ***** ********** to ** ******* *** reduce ********** ** *** system ******* ********.
• ** ******** *********:** *** *****, ******* photos ** * ****** of ******** ** ****** displayed ** ****** ******* could ** **** ** trigger *********** **** ********** nearly ** **** ** the ******* ********** ******** the *****.
• ********* *********** ** *** light:** *** ***** (~* lux) ******, ********** ******* noticeably, **** *********** **** reliable ** *******, ****** angles.
• ******** ****** ** ****/** scenes (~*.** ***):********* *** *********** **** able ** ****** *** recognize ******** **** **** directly ******** *** ******, using ******* ******, ** the **** **** ********** IR ** (~*.**). ******* angles ** ******** ******* down ****** ******** ****** misses.
• ****** ********* ******* ***********:** *** *****, ***-*** models ********** ****** ************ of ******** ******* ****** backlight, ***** **** *** models ********* ********** ******* to ********, ****** *** scenes.

Significant ****** / *********** ********* ******

************, ***** **** **** key ********* ****** ** the ********* ****** *** its *** ************:

• ******** ****** ** ******:*********'* ****** ** *** difficult ** ***, **** multiple ****** **********, **** as ******* ******, ************ terminology, ******* **** **** over ******* *****, ** elements ********* *** *** visible ****, ******* *********, and ****.
• *** ************ *** ** date ********:*********** ****** ******** ** VMSes **** ** ********* or ******* ******** *** of **** ********. *** example, ** ****** ****, Anyvision ******** **** ********* XProtect **** ** *** 2018, **** **** ******* expected ** *** *** of *** *******. ************, Genetec ******** ****** *.* is *** **** ****** supported *******, ***** *** been ********** ** *.* since ***** ****.
• **** ******** ******:** *******, ********* **** not ******** ***** ***** for ******* *********/***********, ********* in **-** ****** ****** prior ** ******* *****. There ** ** ****** to ************* ****** ****** for ******* *********, *** this ***** ****** ****** resources ** ****** ******* systems.
• **** **** ******** ******:**** *********'* "**** ****" was ******* (******** ** blur ***** ***** **** the ****** ** ******** in *****), ******** *** download ** ***** ***** totally ******. ********* **** this ** ******** ** some ********* ***** ****** resources *** ******* *****, but ** ******** **** when **** *-* ******* were ***** ** *** server.
• **** *********** ****/** *****:********* ********** ** ** cameras ***** **** *** does *** ******* ***** or *************.

******* ** ***** ******, and ***** ** *** discussions **** *********, ** is ****** **** *********'* technical **** ** ****** to ** ******* ******** in *** ************** ** properly ***** ***** *** address ***** ****** ** they *****.

*******

******** ** ****** ** $2,500 *** *** *******, not ********* *** **** of ****** ********. ************, NVidia **** *** ********, increasing **** ******** ** typical *******. *** *******, the ***** **** ********* in *** **** ****** sells *** **** ~$*,*** USD *** ******* ~* 1080p *******. ** ****** systems ***** ***** ***** add ** ******* ** multiple **** *** ****.

UI ********

*** ********* ** ** separated **** ******* ****:

• ****: *** **** *** displays **********/************ ** **** occur, *** *** ** scrolled ** **** **** events. "****" ********** *** delayed ** *-** *******, depending ** ****** ********** load.
• *********: *** ********* *** allows ***** ** ****** images, ****** ** ***** streams **** ***** ** integrated (*** *****) ** detect *** ********* ***** from ******* *******.
• ******: ****** ****** ***** to **** ****** ** camera, ** *******, ** those ******** ** ******** image ****.
• ***** ****: *** ***** list *** ** **** for ********** ** ***** lists, ***** *** ** manually ***** *** ** a ****, ** ****, or ******
• ********: *******, *** ******** section ** **** *** adding/removing *******

** ****** *** ****** of *** ********* ****** in **** *****:

Configured ***** ********* ***************

***** **** ********* ***** an *********-******** ****** ***** their *********** ********. **** cameras **** **** ***** default ********, **** * threshold ** *.** *** recognition *** ******* **** size ** **. **** cameras **** ********* ** face ***** ** **-** to ******* *********** ******* as ***********.

***** ****** ***** *******, detection *** *********** ******* improved **********. ***** ******** were **** *** *** examples *****.

Relatively ***** ****** ****

** *** *****, ********* cameras ******** ***-*** ****** subjects **** *** ****** of **** **** * month ** *******, ********* 15+ **** ********* *** contractors, **+ ********* ** other ********** **** *** offices, *** ***+ ******** to ****** **********. *** known ******** **** ***** to *********'* *********, ***** with ***** ********* ******* from ***-*** ****** ****** of **** ********.

*******, ***** ********** *** relatively ***** ******** ** most ************ ********* ** likely ** ** ***********, such ** ******* **** several ******* ********, **** staff *** *******, ******* with ********* ** ********, and **** ******* **** thousands ** ****** ********. Results ** ****** *********** may ****, **** ***** recognition ****** **********.

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

** ***** ******* ******, Anyvision *********** *** *****, with **** ********** *********** of ********, **** ** this **** *** *****:

**** **** ******** ****** down ** *** ***** or ***** *****, *********** was ***** **** **** this ********** *********.

*******, ******** *********** ** outdoor **** ******* ****** were ************ **********, ******* shooting **** **** ****** toward *** ******* (******* at ~*' ******) *** with *** *** ************ the *****.

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

** *** *****, ********* was **** ** ********** recognize ******** ** ~**-** PPF ** **** *** scenes, ***** ***** ******* than **** ***** *********, generally ********* *** *** or ****. *******, ********* and *********** ******** ******* decreased ** **** ***** conditions, ******** *****.

Recognition **** **********/*****/****

**** ******* ****, *****, or *******, ********** *** reduced, *** *********** ***** possible ** **** *** scenes. ********** ********** ****** from ~*.** ******* * hood ** ~*.** ******* sunglasses.

Scarves/Masks ***** *********

*******, ** *** ***** Anyvision *** ****** ** detect ***** **** ******** wore ***** **** *** lower **** ** ***** face, ********** ** ***** conditions ** ********.

No *********** >**° ***** ** *********

***** **** **** ****** detected *** ********** **** only ***** ** ********* was >**°, *********** ******* only **** ** *** subject's ****, *.*., * person ******* ****** *** scene. **** *** **** in *** ***** ****** and ********** ** ***** settings.

Reduced *********** ** *** ***** / **** **** **

******** *********** *** ***** possible ** *** ***** settings (~***), ** *** not ******** *** ** the ********* ******* ***** in *** *****. ****** walking ******* *** ***** were ********** ** *** tilt ******/******* ******** ** the ****** *** ********** dropped ~*.** - *.** points ******** ** *** full ***** ********. *********** at ****** ****** ** incidence/downtilt ****** *** ** the ********** ******* ***** threshold.

** **** ****** **** IR ** (~*.** ***), detection ** ***** *** only ******** **** ******* downtilt *** ******** ******** walking ****** *** ******. Confidence ****** **** ~*.**-*.** lower **** ******* **********, greatly ********** *** ********** of ***** ***** *********.

Wide ******* ***** ******

**** ******* ** **** dynamic ****** **** ** the ***** **** ***** in *** ******* *****, true *** ******* **** consistently **** ** ********* subjects. *******, ***** ******* true *** ** ********** poorly ***** ****** ** recognize *** ** **** cases ******.

*** *******, *** ********** below *** ***** ** the **** **** **** a **** *** ****** and * ***-*** *****. The ***-*** *****'* ********** score ** ****** *.** lower **** *** **** WDR *****, ********* ** a ****.

Few ***** ***************

****** **** **** * month ** *******, ***** identifications **** **** **** when ********* *********'* *************** and ***** ***** ******* confidence ******* ** *.**.

***** ************ **** **** common **** ********** **** harsher **** ****** (**** as ********* ****** *****), resulting ** ********** ********** scores (*.*** *****, ********* 0.55).

Pictures ** ***** ******* ***** *********

** *** *****, ********* consistently ******** * ******* picture ** * ***** recognition ** * ****** when **** ** ***** of *** ****** ** placed **** ******* ******'* face, ***** *****.

*** ********** ***** ** these ************ *** ****, in *** ***** ** normal ********** ** *** actual ****** ** ******** in **** ***** (>*.**).

**** ***** ***** ****, Anyvision ****** ************ ************ *** **** ** the *** **** *** surveillance *** ****:

*** ******* ** *** Better ******** ****** ** to ****** *** ********* all ***** ** *** FOV. *** ***** ***-***** like ****** *******, ** have ******* ******** ********* sensors **** *** ******** by **** ******** *** hardware ** ********* ** a ****** ******** ** front ** * ****** is **** ** * printed/casted *****.

***** ******* *** ********* not ********* ********* *** are ** *** **** some ******* *** ***** of *******. ********* ****** that ***** ******* **** be ********* "****."

Live **** ********* **** ***-***** *******

***-***** ******* **** ********** detected ** *****, ********* wheels, *****, *******, ****, mailboxes, *** ****. *******, these ******* **** ******** with *** ********** *** never ********** ** * subject ** *** *****.

********* ***** **** ***** lower ******** *** ********* faces ******* ***** ** be ******** ** **** difficult *********, **** *** trade-off **** ********* ***** will ** ******** ** inanimate *******.

********* ********** **** ********* objects ** ***** ** the ****** **** (** clicking * ****** ** the ********* ****), **************** ****** ********** ** the ****** (****** ** times ******* ***** *****).

*******, ** **** *** prevent ******* ******* **** being ********, **** ** tires ** ****** **** different ********, *** **** it ****** **** ********* of *** ****** **** the **** ****, ** users **** ******** ****** every ******** ********.

UI ******

*************, *********'* ****** ** was ********* ** ***, with ******** ****** ******** at *** ***** ******, such ** ******* ******, inconsistent ***********, ******* **** tips **** ******* *****, UI ******** ********* *** the ******* ****, ******* functions, *** ****.

***** ********* *** ****** to ******* ******** ** an ********* *******, ***** issues *** ****** ** cause *********** ***** ********** users ** ***** *** to *** ******.

** **** ** **** of ***** ****** ** this *****:

Playback ****** ***** ******* ********

** *******, ********* **** not ******** ***** ***** for ******* *********/***********, ********* in **-** ****** ****** prior ** ******* *****. There ** ** ****** to ************* ****** ****** for ******* *********, *** this ***** ****** ****** resources ** ****** ******* systems.

** **** ** **** issue ** **** *****:

GDPR **** ******

********* ******** ** ****** for "**** ****", ** which ***** ** ******** other **** *** ****** of ******** *** ******* when *******/*********** *****. *******, we **** ****** ** test **** *******, ** our **** ****** (********* and ******** ** *********) would *** ****** ***** when **** **** *** enabled. *******, ***** ********* simply ******, **** **** error ******:

Current *** ******* *********** *** *********

*** ** *********'* ******** to ** ****** ********* above ** ***** ***** VMS *********** ** ******** VMSes, ********* **********, *******, and ****. *******, ** were ****** ** **** these ******** ** ********* does *** ******* ******* versions.

** *** **** ** our **** ** ****** 2019, ********* ******** ********* XProtect **** ** *** 2018, *** **** *** yet ******* **** **/**. Additionally, ******* ******** ****** 5.7 ** *** **** recent ********* *******, ***** has **** ********** ***.* ***** ***** ****.

************, *** *** *********** is ******* *** ****** challenging *** **** *********** integrators. *** ********, *** Milestone *********** ******** ******** components **** ** *** XProtect ***** ******, ******, and ****, ***** *** not ***** ****.

RTSP *********** **** / ** *****

****** *********** ** ********* is ********* ***** **** streams ****. **** ** not ******* ***** ** any ********* *********. ***** must ***** *** **** stream ***, ********, *** password *** **** ******.

Versions ****

********* *.** *** **** in *** *****.

******* *** ********* ***** cameras **** ********, ****, Bosch, ******, *** *********.