Using PHP to Capture Camera Stream and Perform Emotion Recognition

Cameras are ubiquitous, and recognizing human emotions through them is a challenging yet feasible task with modern AI. This article demonstrates how to operate a camera using PHP and analyze emotions via facial expression parsing.

Preparation : Ensure the server has appropriate camera drivers and PHP libraries installed. On a Linux system, install the PHP GD extension and V4L2 utilities:

sudo apt-get install php7.4-gd

sudo apt-get install v4l-utils

Obtaining the video stream : 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 "
";
?>

The code captures a frame and displays it on a web page.

Emotion recognition and facial analysis : Integrate the open‑source Fer2013 model to classify emotions from the captured image. A PHP wrapper calls a Python script that loads the model and returns the predicted emotion.

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

Complete example : The combined script captures a video frame, runs the emotion classifier, and outputs both the image and the detected emotion on the page.

Conclusion : By following these steps, developers can build a simple PHP‑based system that accesses a camera, captures images, and performs basic emotion recognition, providing a foundation for more advanced applications.