Key ********
****** *********** ****** ********* accuracy *** *** ****** than *** ****** ****** including ****** ** **** of ********:

*** ****** *** ********* quite '***' *** **** of *** ******** ** used **** ***** ****, including *** ********* *** bad ******.
*** *******, **** ** segment *** ****** ** key ********** ****, **** for ****** ***********, ***** differences ** *********** ******* are *******:

**** ******* *** *** severe ****** ******** ***, with '****' ***** *********** at ****** **% ***** low ***** *********** ** under **%.
***** *********** *** ********* in ****** ********* ********, it ***, *** *** away, *** *******, ** two ****** ** ********* versus ******** *** **** running ** ** **:

*********** ** **** ****** than *** ***** ******** as *** *********** ***** service ******** *** ***** to ** **** ***** to *** ***** *** other ******** *** ** done ******* / ** the **** / ***** the ****** **. ** examine ***** *********** ******* in *** ***** ******* of **** ******.
********
*****, ** ******* ** 100% ******** *** ****** Rekognition, ***** ** ****** strong *********** *** **** is **° **** *** 45° **** **** **** the ******:
![[video-to-gif output image]](https://placeholdit.imgix.net/~text?txtsize=30&txt=Premium+Content&w=640&h=300)
****, ** ******* ** 59% ******** (******* ~* out ** ** ****** correctly ******* * ****) for ****** ***********, ****** a ***** ********* ** steep **** *** **** tilt **** *** *******'* head ****:

*** ***** ******, ** noted, **** **** **** challenging **** *** ***********. For *******, **** * out ** ***** * frames *** * **** accurately ******** ****** **** a ***** ***** *** the ****** / ********:

*******, *** ** *** few **** ************ *** Rekognition *** ** **** test ********, ****** *** light, *** ******* ****** straight ******* *** ****** but ***** **** *** not ******** ** ***:

Accuracy ***********
*** ******** ****** **** is ************** *** * simplification. *********** **** ********* evaluation **** * ****** called"**** ******* *********" (***), ***** ******** ***********-**-******* on ****** **** ********* datasets ************** ** ****** **** bounding-box ******* (********* ****** "Intersection **** *****" ** IoU) *** ******* **** box ********* ******** * face. ** ****'* ***** library, **** **** ****** has *** **** (***** frame *** * ****, and ***** ** **** one). ***** ****, ** can *** * ****** heuristic *** ********: ** how **** ****** *** a **** ******** (******** / *****-***** = ********). This ** *** *******: in **********, ** **** not ******* *** ***** positives (* **** ** detected ***********, **** ** the **** ** ** the *******'* *****). **** happens ****** - ** we ***** **** *** heuristic. ** ****** ** more ******* **** ********** (lux, *****, ***) ******* having ** ***** ******** boxes *** ***** ***** of *** *******.
FPS ***********
*** ******* **** ****** used *** *********** ***:
- ****** *** ***** ** Amazon **
- ***** *** *****
- ***** *********** (******** ** to *** ** ****, registering *****->***********)
- **** *** *****, ********* FPS
* **** ****** ******** for ************ ***** ** to ****** ****** ******** via*******->***********. **** ***** *** the ********** ******** ** a *****-**-***** *****, ***** our ***** ***** *** networking ******** **** *** FPS *********** ********. ** such, *** *** ***********, already **** ***, ***** be **** *****.
***** ** **** ************, this ** * ***** point ******* ***********, ** others ** *** ** a *******. *** *******, one *** *** ***-***** hardware *** ****** ******* performance. *** ***** ****** in **** ******* *** on ****** * ** Intel ** ******* (****-***) devices, ** **** *********** trade-off ** *********-*********. ************, Rekognition ** * ******* service, ***** *********** * model (**** ********'* ****-******-****) takes **** ************* *** setup. ** ***** ****-**** performance **** *********** ** unlikely (****: ** *** still ************* ** **** is ********), *** ***-****-**** applications, *********** ***** ** quite ******.
*******
*** * ****-**** ***** surveillance ***********,*********** ************ ** ***** **** but *** ***** ************ where **** ********** ***** processing ** ******, ** could ** *** **** affordable **** **-**** **********. For *******, *********** ******* for **-**** (*. ********) is $*.** *** * min ** **** ****** video ********. **** **** just **% ******** ** analyze (*.*., *,*** ******* in * *****), *** monthly **** ***** ** ~$50 (*,*** * **% x $*.**) **** *** the **** *********.
** *** ***** ****,****** *********** ****** ******* features********* ****** ***********, ****** analysis (***, ******, *******), object *** ********** *********, etc. **** **** ********* provider ****** ** *** have ** ***** ** likely ** ******** ** compete **** ***** ***********.
********
**** ** *** *** of ****'* *** ****** of **** ******** *****, starting ********** ********* ******,***** ****** ******* ***** 2 / ******** ** Test*** *** ****. ** are ******** * ******* of *** ***** ** the ******** ******. *** feedback, ******** ** *********, please *** ** *** comments.
Comments (8)
John Honovich
For those of you interested in the fundamentals, check out our new class next week:
Tyler will be explaining fundamentals as part of our parallel effort to provide comprehensive training and education, in addition to our ongoing tests.
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Undisclosed Manufacturer #1
Was any testing done running the algorithms with IR nightvision on? Most cameras would switch to IR nightvision (if they have the option) at 1 lux
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Matthew Del Salto
12/03/18 03:12pm
Just wait until they integrate it with Ring if they haven't already.
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Undisclosed #2
Is there any way you can post all of your raw video used in the tests for IPVM users to download and run thru their own Analytics systems?
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Undisclosed #4
Aren't you considering the "10%" factor twice in this calculation? 4,380 minutes itself is 10% of total minutes in a month.
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