*******

******** ****** ******** ***** in *** ***** ******** platforms, **** ***** ***** synopsis *** ******** ********* speeding ****** ************* ******** to ******* ***, **** features **** ** *****, clothing *****, ******* ****, direction, ***., ******* ************ well ** ******* *** moderate *** ***** ******, useful *** **** ********* and **** ******. ************, its ****** *********** ********* were *********** **** ****** we **** ******, **** as ********* *** ********, with ** ***** ************ in * ***** ** testing.

*******, ******** **** ** age *** ****** ******** were **********, **** *** detected ** ***** *** adults ******** ** ********, and **** *****. ************, frequent ****************** ** ********* objects (****** ***** *** large *******) ** ****** will ****** ****** **** analytic *********** ** ******* scenes.

*******, *** *****, **********, and ****-*** ******** ************ (at ***** *** **** required) *** ** *** of *** ***** ** many ***********, ****** ** most ****** * *** in ****-*** **********, *********, or ********** ********, ***** is ***** *** ******* has ************ *******.

Vs. ******** ********** ******

******** *** ***** *** advantages ******** ** ********:

• ***** ********:********'* ***** ******** ** its **** ********* **** Avigilon's ********** ******, ** it ****** **** ****** review ** ******** ***** compared ** ****** ******** or ********* ******** ******** in ******** ******* ******.
• ***** **** ** ******:************, ******** ****** ******** faces *** ********** ** be **** ** * search **********, ***** ******** only **** ****** *********** in **** ******.
• **** ********:******** ********** ****+ ******* ******** *** ******* video *** ******* ****** (including ******* *** *********) for **** ******. ********'* Appearance ****** *** ****** recognition *** ****** **** with ***** *** *** VMS.

*******, ******** *** **** advantages **** ********, ** well:

• **** ******** ****** *********:***** ******** ******** **** false *************** ** ********* objects ** ******,********'* ****-******** ************* **** **** ******** in *** *****, **** few ***** ****** ** animals, *******, ** ****, making **** **** ********* useful *** **** ******.
• ***** ********** ******:************, ********'* ********** ****** is ***** ********** ** its ***, ** ***** may ****** ******** ******** directly **** **** ** recorded *****. ** ********'* integrated *****, ******** *** performed ******* ******* *** embedded ******** ******.

Vs. *********

** ***** ** ****** recognition ********, ******** *** Anyvision ********* ********* ** our *****, **** **** few ** ** ***** recognitions (*** ******* ******** for *******). ********* *** moderately **** ******** **** subjects **** *******, *****, or ***** ***********, ****** BriefCam ********* ****** ** WDR *** *** ***** scenes.

*******, **** **** ********* does *** ******* *** video ******** ** ******* object ******* ** ********, such ** ********, *****, direction, ***, ***** **** BriefCam **** ********* ****** for ******** ******.

Key *********

******** *** ******* ********* in *** *******:

• ******* ****** ****:********'* ***** ******** *** forensic ****** ******* *** time ****** ** **** specific ******* ** ******** in *** ****, ** the *********** ** ****** video ****** *** ****** filters ****** ******** ******* from ******.
• ******** ****** ********* ****:****** **** **** ** color, ******** *****, ******** detection, ********* ** ******, object ****, *** ****** accurate ** *** *****, features *** ***** ** most, ** ***, *********** analytic *********.
• ***** **** ***:********'* ****** *********** *********** was *********** **** ******, as ****, **** **********************'* ********** ******, **** ** ***** recognitions ** ***** ***** of *******, ****** **** moderate ***********, ******** *****.
• ******** ******* **************:******* ****** **** *** very ******** ** ****, identifying ***** *** **** (car, *****, ***, **********, etc.) **** **** *** misclassifications.

*******, ******** ******** **** multiple *********, ** ****:

• ********* ******* ********** ** people:** *** *****, ***** animals, **** ********, *** blowing ***** **** *** regularly ********** ** ******, regardless ** ******** ** optimize ********.
• ********** ***/****** ********:****** **** ********** ** children *** ***** ** men (*** **** *****) in *** *****.
• ******** **** ********: ******** ******** * minimum ** ** ***** two **** ********** ****, as **** ********* *** synopsis/forensics ****** ** *** simultaneously ** * ****** GPU.

Video ******** ****** ******

***** ********'* ***** ******** significantly ******* *** ****** of **** ******** ** review ***** ********** ** video *** ******* ******* the **** ******** ** find ******* ** ******** across *** ** **** cameras.

** **** ** *** synopsis ** *******, ***** with ****** ******* ***** may ** *******, ** this *****:

Most ******** ******** ********

** *** *****, ***** analysis *** ********* ********. Searching *** ******** ******* red **** ******* ** accurate *******, ****** **** trial *** ***** ** selecting ***** *** ** required.

************, ***** *** **** sleeve ********* ****** ******** to ****** **** ******* further ** ******** *****, e.g., *** "***** ***** sleeves" ****** ***** ****:

************, ********* **** ********* accurately ********, ***** ****:

Age *** ****** **********

****** *** *** ************** proved ** ** *** most ********** ************** ** our *******. *** **** long **** **** ********* classified ** *****, ***** below.

************, ****** **** ******, many ****** **** ********** as ******** ** *** tests.

***** *************** **** ********* inaccurate ** ********'* ********** Search, ** ****.

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

******** ************** ******* ******* types, *********: ****, *******, trucks, ****, *****, ******, boats, ********, *** ***********.

******* ******** *** ********, as ****, **** ** the ***** **** ***** below.

*******, ******* ***** *** inaccurate ** *** *****, with ********** *********** ******* many **** ** ****** appear ** "***."

Direction / **** / **** ********

******** **** ****** ***** to ****** **** ********/****** by ****** *********, * drawn ******** ****, ** area *******, *** ** which **** ******** ** our *****. *** *******, the **** ***** ***** pickups ********* ** *** right ** *** ***.

** ******** ** ****** direction, ***** *** **** draw * ******** **** on *** ******'* ***** of ****, ********* ****** to **** ***** ****** along **** ****. ** our *****, **** ****** accurately, *** ***** ** useful ** ****** ***** only ** ***** ******* which ******** **** ***** path.

** *********** **** ******* in **** *****:

Natural ******** ****** *** ******

** ******** ** *** main *** ****** **, BriefCam **** ****** * mobile *** ***** ****** users ** ****** *** objects ***** ******* ********. For *******, * **** may ****** **** "****** in *** ** **** hour" ** ***** * search. ******* *** ******** in *** *** *** also ****** ** * case ** *** ****** for ***** *********.

** *********** **** *** in **** *****:

**** ******* *** ************* is ********, ******** * simple *** ** ******** searches **** * ****** device ******* ******** ** app's **.

*******, **** **** ***** searches *** *** *******, but *** ******* ****** for **********. ********* *** days ** ***** **** ~10 ******* ** *** testing, **** *** *** notifying ** **** ** was ********. ******** **** appear ** ********'* **** UI ** **** *** be ********* *** ********* from * ********* ******.

No ********** ***** **********

***** * ******** ** over *** ****** ** over ***** ** *******, no ******* *** ******** for ******* ****** ** the ***** ****.

** * **** ***** setting, ***** *** ********** detected ** ~**-** *** or ~**-** ****** *** face, **** ** ***** than ********* ***** ******** ~85-90 *** *** ******** Facial *********** ***** ******** ~90 ***, **** ******* lower **** **** ***** platforms ********* ********* ~*** PPF *** ******** ***********.

Face *********** *********** ******** ** ***** ******

** * **** ***** setting, **** *********** ***** not ***** * **** to *** ***** **** at * *' ****** and ~**° ******** **** the ******* ********** ** an ***** (~**° ***** of *********).

** ******* ******, *********** was *** ********, **** as *** **** **° angle ***** ****. **** that **** ****** *********** platforms ** *** ****** at ***** ******, **************'* ********** ********* **** **.

Performance ********* ** *** ***** *** ****/**********

****** **** ***** **** to ** ********** ** low ***** ** ****** camera ******* ** ~**' and ********* ** ~**° but **** **** *** lowest ********** *******. *********** was **** ******** **** low ********** *********** ** a **° ***** ** a *** ****** ****** of *' *** **° downtilt.

*********** **** *** *** similar ** * ****/********** setting ** ~*.****, ****** camera ******* ** ~**' with ~**° ** ******** resulted ** *** ********** detections *** **** ***** camera ******* ** ~*' with **° ******** **** recognized **** *********** ** a **° *****.

Low ********** *********** **** ***/**** *** **********

****** *******, **** ** a *** ****** ****** of ~*' **** **° of ******** ****** ******* wearing *********** **** ********** parts ** *** **** (e.g. ********** *** * hoodie, ***** *****) **** only ********** **** *** lowest ********** *******.

People ******** ******** ********, *******, *** ********

****** *******, ****** **** properly ******** ** ****** walking ****** *** *** night, ** **** ** when *******, ********, ** partially ********, ***** ****:

People ******** ** ~* ***

** *** *****, ****** were ********** ******* ** at ~* ***, ***** a ***** ****** **** a ***° ***** ** view **** ******** ** a ~***' ********* ********. This ** ******* ***** than ******* *** **** performing ********* **** ** Avigilon's ** (~** ***) or ***** *** (~* PPF).

False ****** ****** ** *********, *******, *** *******

********* ******** **** *** camera's **** **** ********** classified ** ******, **** when ***** ****** ********** requirements.

******** ** **** ******** in *** ******** **** stamping **** ***** ** the **** *** *********** them ** ******, ***** visually ********* *** ******** during **** ******, ****** it **** ********* ** review.

***** ******* ******* ******* the ***** **** ** deer ** ***** **** were ********* **** ********** as ******, ***** ********** of *****/******/****** ********** ********.

*******, ******* *******/***** *** classified ** ******, ** well, *** ***** ***** not ** ******* ** using ******** ********.

BriefCam ******** ** ******************

**** ***** ***** ***** false ***************, ******** ********* that ***** ******** ** not ******* ** ****** them. *******, ***** ******** is ** ******* ***** objects *** "****** *********" to ********* ** **** may ********* ** ******. Additionally, **** ********* **** events *** ****** ** relevance ** ******* *** these *************** ********* *** not ***** ** **** confidence, ** ***** ** the ******* ******* *****.

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

******** ** ***** **** to ******* ************** **** large ********** ** ***** – ** ** ******* months **** ******** *******. As * ******, ***** conduct *** ************* ** reviewing *** ******** ******* via ***** ********® ** thumbnail **** ****** **** viewing *** ******** *****. Therefore, ** ** ******** that ** ** *** miss *** ********* ** any ******* ** *** scene. ******* **** ** are ****** ** ******** correctly (******* ******* ** have *** ******* *** DNNs **** ******* ****) are *** ********* ** ensure ** ** *** miss ********* ******. *********, an ************* ************ ** obtained ** *********** * subtle ******** **** ** hardly ************ *** ************ by *** ***** ***; raindrops **** **** **** category. ******** ************ ******* many ***** ** ****** objects **** ** ****** leaves, ***** *********, ***** graininess *** ******.

*******, **** ** ******* to*********'* ******** ** ******* inanimate ******* ***** **** detected ** ***** ** operators, ******* ** ******** every *** ********** *********, as ***** *** ** removed ***** ***** ********* be ****** ** *************.

VMS ****** *********** *******

********'* *********** ** ***** is ****** ******* ** reproducing *** ******** ** in *** *** *** or ******** * ******** to ** ******** **** VMS *******, ******* ** integrating ****** ******** *** search ********* **** *** VMS ****** *******.

******** ***** **** **** to **** ***** (*******, Indigovision, *** *********), ** any **** **** ** smart ***** *** ** used ** ******* ** alarm, ***** **** ** object ********, **** ** a **** ** *******. However, ******** ****** ******** such ** *****, *********, speed, ***., ** *** sent ** ****** ** the ***, *** ******* available ** *** ******** client.

** ****** ********* ******** Smart ****** *********** ** this *****:

** ******* ** * Milestone *****:

***** ****** *********** ** limited, *********** ***************** ** ******** ****/******** video *** ******* **** other ********* ** **** tested, **** * ****** installed ** *** ******** server, *** *** ****** credentials *******, *** ****** other *****.

High ******** ************

****** **** ******** ********* we **** ******, ******** requires ** ***** *** GPUs ** *** *** full ***** ** ********, as **** **** ** dedicated ** ****** ****-****/**** alerts ** **-******/***** ******** processing. * ****** *** cannot ** **** *** both.

**** **** ********** ******** to ****** ***** ******* processing ** * ****** GPU. ******** ******** ***** cost **** **** ******, such ** *** ****** GTX ****, ***** ***** for ~$*** *** ******, which *** ****** ******** cost *** **** **** for **-****** **********. *******, for ***** *******, **** expensive ****** *** ***** GPUs **** ** ****, similar ** ******** *** Anyvision ************.

******** **** *** ******* exactly *** **** ******* a ***** *** *** handle, ** ** ******* on **********, *********, *** bitrate. *** *** **** in *** **** *******, the *** *** ** BriefCam's ************, *** **** to ******* **** **** alerts *** **** ~*-* 1080p *******.

*******

******** ***** ** ******** only *** ~$***-*** *** per *******, **** * 100 ******* ******* ***** (~$25,000 **** ****). ************, at ***** *** **** are ******** (*** *** real **** ******, ******* for ******** **********), ****** ~$2,000+ ** ********.

*** ******* *** (~$**,*** USD **** ****) ** available *** ******* ******* counts, ***** ******** ****** hardware *** *********.