Avigilon Appearance Search Tested

Executive *******

***** ** *** *****, Appearance ****** ******** * significantly ****** ***** ** search *** * ******** person ** ******* ****** multiple ******* ******** ** using ******** ** ********* search *****. *******, ***********/******** identifiers **** ** ***, gender, *** **** ***** were ******* ********** ** our ***** *** ********** IR (*** ********* ******) ****** ************* ** objects *** ****** *****/****.

Key ********

** *** *****, ********** Search *** ******* *********:

• ****** **** ******* *** search:***** ********** ****** *** significantly ****** **** ********* through ********* ** ***** typical ********* ******, ********** across ******** ******* *** multiple ****.
• ******** ***** ****** *******:********* *** ***** ** lower **** ***** *** generally ******** ** *** tests ** ******* *** moderate *** ***** ******.
• ******** ******* **************:********** ****** ********** ********** and ******** ******** ******* types, ********* ****, ******, buses, *********** *** ********.
• ****** *************:** *** ********** ******, users ****** ***** ** box ** ****** ** on **** ******. ** further ************* ** ********.
• ** ********** **** **** ACC:********** ****** ** ******** with ******** ******* ****** Enterprise ** ** ********** cost. ** ******* ********* is ********.

*******, ***** **** ******* drawbacks, ** ****:

• ********** *********** ***********:********* ** ****** ** age (*****/*****) **** **********, with **** ******** ***** as ****** *** **** versa *** ****** ***** as ******** *** **** versa.
• **** ***** ** **** hair ******:**** ********* ***** ** black ****, ******** **** hats **** ********** ***** in ****** *******.
• ********** ** *** *******:** *** **** **** IR **, *** ******* effectively ****** ***** ** gray, ******** *** ****** they *** ** ********. Results ** ******** ******** in ** **** **** less ******** **** ***** in ***** ******.
• ********** **** *******:** *** *****, ********** Search ********* ******** ********* objects (***** ** *****) or **** **** ** a *******'* **** **** adding ** *** "**** Profile." ***** ******* ****** be ******** ******** ** disregarded.
• ******** ********* ****:********** ****** ***** **** with ********'* *** *********, not ***** *******, ************/********** ** *** ** their ********* ********** (* significant ********** ****).

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

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

** *** *****, ********* upper *** ***** **** clothing ****** *** ******** during *** *** *** in ******** *** ***** (~1-5 ***). ******** ****** were **** ******** (***, yellow, ******, ****) *** brown, ****, ***** **** accurate, ** ****.

Subject ****** ********* ********

********* * ****** ** a ******** ******* **** recorded ***** *** ********* accurate ** *** *****, with **** ******* ******* the **** *******. *** example, ******* ***** **** the ******* ** *** different ******* ** ***** different *****.

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

********** ****** ******** **** detection ** *** ********* of ****** ******. ** a ****** *** ******** a **** ********** ******, it ** ***** ** the *******'* ********** ***********, shown *****. ** *** tests, **** * **** was ********, ******** *** generally ******, ********** ****** multiple **** *** ******** changes. *** *******, *** subject ** ******* ***** different ******/**** ** **** image:

*******, **** *** ** confusing *** ***** ** there ** ** *** to ******** ****** ***** faces ***/*** *** *****, there ** ** ********** of ******* * **** is ** ** *** detected, *** ***** ****** be ***** *** *****. This **** ********** ** ** ********** parameter ** *** *******'* appearance, ******* ** ******** color, ******/***** *****, ***.

************, ***** ** ** way ** **** * face ** "*****" *** tell ********** ****** ** exclude **. **** *** be ** ***** ** the ******** ************ ******** inanimate ******* **** ** the ***** (**** *****) or *****, ***** ****** be ******* **** *** subject *******.

Searching ***/****** **********

**** ********* ***** ********, searching ** *** *** frequently **********, ******* ****** adults **** ********* *** children.

************, ********* ** ****** was **** **********, ********* mostly **** ******* **** high ********* **** ***** were ********.

Searching **** ***** **********

********* **** ***** ******** false *******, *** ******* searching ******* **** ***** hair ***** ******* ******* of ****** ******* ***** hats, ********* *** ****** people ***** **** ******.

Accuracy ******* ** ** ******

********* *** ******** ** dark ****** **** ********** IR ** ******** **** accurate ******* ** *** subject's *****(*) *** *** be **********. *** *******, despite ***** ****** ** the ******* ** ** below, **** ********** ******* of ****** *** *****.

Accurate ******* ****** *** ***** / ****

** ******** ** ******* clothing, ******* ***** ****** also ****** ****, **** red **** ***** ***** over *** ****** ** several ****.

******* **** *** **** accurately *********, **** ****** and ***** ************** **** cars:

*** *********** ********* ********** differentiated **** ******** ** other ********:

Simple *****

** *** ** ********** Search, ********'* ********* ******* must ** ********** *** installed ** **** ****** (~5 ****** *******). ***** installation, ********** ****** *** be ******* ** ******* cameras.

Pricing / *************

******** ********** ****** ** included ** *** ********** at ** ********** ****. Users **** **** ******** one **********'* ******** ******** *** ** a ***** ***** **** server **** ********* *** (Nvidia ******* ** ******).

********** ****** ***** **** with ******** *********, ****** from*** (*** *** ****)**** *********** ** ************ ***** ***** *******.

********

******** ******* ****** *.*.*.** was **** ** *******. Nine ********* ** *** H4 ******** ******* **** used ** *******, ********* bullet, ****, ***, *** multi ******.