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Performance on Raspberry Pi for detecting humans

asked 2012-12-20 14:22:20 -0500

Tie-fighter gravatar image

I would like to detect and track people using a Raspberry Pi, Model B v2 (512MB RAM) and a Logitech C310 webcam on a pan/tilt mount.

I experimented with the BackgroundSubtractorMOG2 which worked quite well, but stitching (to build a background for the entire range of vision) is to slow.

Now I am considering:

  1. Using BackgroundSubtractorMOG2 without stitching and only moving the camera in discrete steps (-45° , 0°, +45°), treating the three FoVs seperately.
  2. Using a fast algorithm for object detection. Maybe LBP?

Is it possible to detect people on a Raspberry Pi with LBP or some other algorithm in real time? Can a neural network be fast enough for this too?

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answered 2012-12-21 03:04:27 -0500

LBP is not fast algorithm, but it works well on Android devices with ARM SoC. You can see Face-Detection sample for Android, but it is written in Java.

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answered 2019-12-10 19:53:29 -0500

TinyYolov2 and TinyYolov3 can go up to ~10frames per second and recognize humans well on the raspberry pi.

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Asked: 2012-12-20 14:22:20 -0500

Seen: 2,054 times

Last updated: Dec 21 '12