Motion Detection Performance Tested

Author: Benros Emata, Published on Sep 05, 2011

Motion detection is an important element of many, if not, most surveillance systems. It plays a central role in both storage search time reduction. Storage is routinely reduced by 30% - 80% by using motion based rather than continuous recording. Likewise, an investigator can often much faster find a relevant event by simply scanning through areas of motion rather than watching through all video.

At the same time there are a number of challenges associated with using motion detection:

  • Scene Conditions: The accuracy of motion detection and the amount of times motion is detected can vary depending on what's in the scene - people, cars, trees, leaves, etc. - and the time of day - night time with lots of noise, sunrise and sunset with direct sunlight into a camera, etc.
  • Performance of Detector: Motion detetion is built into many surveillance products - from DVRs to VMS systems and now IP cameras. As such, how well each one works can vary significantly.

Our Test

In this report, we share our results from a series of tests we performed to better understand motion detection performance.

We did a series of tests in different locations:

  • Indoor well light scene to simulate the simplest scene possible
  • Indoor dark scene (<1 lux) to examine what problems low light caused
  • Outdoor parking lot to see how a complex scene with trees, cars and people would perform
  • Roadway to see how a moderately complex scene with periodic cars would perform

Three IP cameras were used with their motion detection enabled to see differences in performance:

With these tests, we answered the following questions:

  • How can one estimate motion percentage accurately?
  • Does motion estimation vary significantly by scene?
  • How accurate was motion detection in each scene?
  • Did certain cameras exhibit greater false motion detection than others? What scenes or conditions drove those problems?

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**** ********* (*:**** - *:****)

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******* (*:**** - *:****)

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********* (*:**** - **:****)

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Other ******* ****** *********

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***** ******* *** & ****** ****** ****/****** ***** (*:**** - 5:30pm)

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***********

**** *** *** ***** (*) ******* **** ** *** '****** Based *********' *****:

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

  • ******* ******** - ** *****
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  • ********* **-***** - ** *.**
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