Using PHP and V4L2 to Capture Camera Stream and Perform Emotion Recognition with Fer2013

Camera devices are ubiquitous, and recognizing human emotions via camera has become feasible with AI. This article explains how to set up a Linux server with V4L2 drivers and PHP GD library, capture video frames using FFmpeg, and apply the open‑source Fer2013 model for emotion classification.

First, install the required packages:

sudo apt-get install php7.4-gd
sudo apt-get install v4l-utils

Then use PHP's shell_exec to run an FFmpeg command that captures a single frame from /dev/video0 and saves it as an image.

<?php
function getVideoStream() {
    $cmd = "ffmpeg -i /dev/video0 -vf fps=1 -s 1280x720 -f image2 -frames 1 /path/to/image.jpg";
    shell_exec($cmd);
    return "/path/to/image.jpg";
}
$videoStream = getVideoStream();
echo "<img src='$videoStream'>";
?>

To recognize emotions, integrate the Fer2013 model by invoking a Python script from PHP:

<?php
function getEmotion($imagePath) {
    $modelPath = "path/to/Fer2013/model.hdf5";
    $cmd = "python3 scripts/emotion_classification.py $modelPath $imagePath";
    $emotion = shell_exec($cmd);
    return $emotion;
}
$emotion = getEmotion($videoStream);
echo "Current emotion: $emotion";
?>

Running the complete example displays the live camera image on a web page and prints the detected emotion, providing a simple entry‑level guide for implementing camera‑based emotion recognition in PHP projects.