ailia Tech BLOG
CrowdCounting : A Machine Learning Model for Counting People
This is an introduction to「CrowdCounting」, a machine learning model that can be used with ailia SDK. You can easily use this model to create AI applications using ailia SDK as well as many other ready-to-use ailia MODELS.
Overview
CrowdCountCascadedMtl is a machine learning model released in August 2017 that counts the number of people in an input image. It is suitable for counting attendance in large crowds such as concert halls or stadiums.
Architecture
CrowdCounting calculates a DensityMap that shows the distribution of the crowd, and predicts the number of people by making estimation based on this Density Map.
Source：https://arxiv.org/pdf/1707.09605.pdf
The output of the high-level prior stage, which is trained using the Classifier model to count the number of people, is input to the Density estimation stage to increase the accuracy.
Source：https://arxiv.org/pdf/1707.09605.pdf
The Shanghai Tech dataset and UCF_CC_50 were used for training and evaluation, and both showed high performance.
Source：https://arxiv.org/pdf/1707.09605.pdf
Source：https://arxiv.org/pdf/1707.09605.pdf
Source：https://arxiv.org/pdf/1707.09605.pdf
Source：https://arxiv.org/pdf/1707.09605.pdf
Usage
To use CrowdCounting with the ailia SDK, use the following command to measure the number of people seen by the webcam.
$ python3 crowdcount-cascaded-mtl.py -v 0
An example of the processing result is shown below.
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