Detect faces with OpenCV on Android Devices
Introduction
Background
Create a project, add OpenCV, and read camera frames
Face detection
Next Steps

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About this Learning Path

Skill level:  Introductory
Reading time:  30 min
Last updated:  05 Aug 2026
Skill level:
  Introductory
Reading time:
  30 min
Last updated:
  05 Aug 2026
Author:Dawid Borycki
Arm IP:Cortex-A
Tags: ML Windows macOS Android Android Studio Kotlin
Author:
  • Dawid Borycki
Arm IP:
Cortex-A
Tags:
ML Windows macOS Android Android Studio Kotlin

Who is this for?

This is an introductory topic for developers who are interested in creating Computer Vision applications with OpenCV on Android devices.

What will you learn?

After completing this Learning Path, you'll be able to perform the following tasks:

  • Describe how you can use OpenCV for face detection.
  • Use OpenCV to retrieve camera frames.
  • Use Haar cascade classifier for face detection.

Prerequisites

Before starting, you'll need the following prerequisites:

Summary

AI-assisted

This summary was drafted with an approved AI-assisted workflow and reviewed by Arm contributors before publication. Human technical review remains part of the process so the final page reflects engineering rigor, accuracy, and Arm editorial standards.

Close
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You’ll build an Android app that performs face detection with OpenCV and a Haar cascade classifier. First, you’ll configure the project, add OpenCV, retrieve camera frames, and load the pre-trained cascade. Then, you’ll apply the classifier to live input. Finally, you’ll deploy the app to a connected smartphone and exercise the detection pipeline.

Frequently asked questions

AI-assisted

These FAQs were drafted with an approved AI-assisted workflow and reviewed by Arm contributors before publication. Human technical review remains part of the process so the final page reflects engineering rigor, accuracy, and Arm editorial standards.

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Which Android Studio project template should I choose to follow the steps?
Use the Empty Views Activity template. It matches the structure expected by the instructions and keeps the project minimal.
How do I know OpenCV is correctly added before I write detection code?
Your project should sync and build without errors, and OpenCV classes should resolve in the editor. You can confirm runtime availability when the app runs on the device without OpenCV initialization errors.
Do I need to train a face detector for this project?
No. You’ll use OpenCV’s pre‑trained Haar cascade for face detection, so you don’t need to train a model.
What cascade file format do I use for face detection?
Use a Haar cascade XML file provided by OpenCV for face detection. It contains pre‑trained data the classifier loads at runtime.
What result should I expect when the app runs on the device?
You should see camera frames retrieved and processed with the Haar cascade classifier. Check for detections according to your app’s processing and display logic.
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