GMU:Tutorials/Performance Platform/Capture with Processing: Difference between revisions

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==Algorithm of calculation==
==Algorithm of calculation==


There are many ways for the computer vision to calculate the capture area to serve for your purpose. To calculate the amounts of people, you may use '''face detection''' or '''blob detection'''. Here, I am going to use blob detection cause there exist the case someone who will walk in front of somebody, then the face will not be well detected by the webcam.
There are many ways for the computer vision to calculate the capture area to serve for your purpose. To calculate the amounts of people, you may use '''face detection''' or '''blob detection'''. Here, I am going to use blob detection cause there exists the case someone who will walk in front of somebody, then the face will not be well detected by the webcam. Blob detection will be great to calculate the amounts of people if we are going to set the webcam on the roof of lab, so that every person that inside the capture area will be detected as a blob.

Revision as of 16:27, 13 July 2016

Introduction

My purpose of this tutorial is about how to calculate the amounts of people in the platform. And due to this platform system is not specifically structured to count the amounts of people, I decide to set my own webcam as an external set to count the amounts of people in a area that my webcam is able to capture.

The tracking system in the lab of course can count the amount of people due to the capture of skeleton of people somehow, however, it has a limitation that only two or three can be counted. So, you can also choose to use the tracking system to count the people if you only want to count the people less than three.

Algorithm of calculation

There are many ways for the computer vision to calculate the capture area to serve for your purpose. To calculate the amounts of people, you may use face detection or blob detection. Here, I am going to use blob detection cause there exists the case someone who will walk in front of somebody, then the face will not be well detected by the webcam. Blob detection will be great to calculate the amounts of people if we are going to set the webcam on the roof of lab, so that every person that inside the capture area will be detected as a blob.