Testing VideoIQ's Video Analytics (iCVR)

Author: John Honovich, Published on Jul 29, 2009

In this test, we examine one of the most discussed manufacturers in video analytics - VideoIQ. Their claims of automatic calibration and self-learning technology has drawn substantial interest. Their most recent product offering, the iCVR, is one of the only products available that integrates a camera, DVR and analytics into one unit.

Challenges with Analytics

Over the last few years, analytic performance has been a hotly debated topic with many users finding disappointing results.

Increasing the challenge was a lack of public independent test results. With huge marketing campaigns but minimal 3rd party technical reviews available, determining what worked and how it worked were hard questions to answer.

Summary of VideoIQ Analytic Test

These are key findings from our test:

  • False Positives in a variety of environments were uncommon. A small number of conditions generated periodic false positives.
  • False Negatives (missing suspects) was generally very low except for a number of conditions that should be carefully considered.
  • Performance was achieved without any software configuration; However, users should recognize system limitations and plan accordingly.
  • Initial start-up and system re-starts created temporary reductions in performance
  • Performance was consistent with technical guidelines provided by VideoIQ. However, some of the more aggressive marketing claims were not consistent with our test results.

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Challenges **** *********

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Summary ** ******* ******** ****

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

Test ***** *** ********

** ****** *** **** **** ** ** ** **** ***** (model ****** ***-*****) ***** *** ** **** ** ************* $*,*** ***.

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Daytime ***********

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Nighttime ***********

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***** *** ***** ** ******** ** **** ******** ************, ***** should ** ******* ***** ********* ***** ******** ********** *** ************* the *********** ** *** *****-** ****** *** ******** ***********. ***** VideoIQ ********** ****** ** ********** ************, **** ** ***** *********** due ** **** ** ************** ***********.
Narrow ***** ** **** ***********

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False ****** ***********

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

Object ********** ****** ***********

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Analytics ************* *** ************ ******

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Contrast ** *******'* *********** ** ********* ******

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Recommendations ** *******'* ******** ************

** * **** *****, ********* ***** ********* ******* ** * criteria:

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  • ********* ** ***** *********
  • ***********/********** *** ******

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