Project Hub /Artificial Intelligence & Edge ML/Object Detection & Tracking/Real-Time Face Tracking Using Raspberry Pi 4 Versus Raspberry Pi 5 With Hailo-8L

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Real-Time Face Tracking Using Raspberry Pi 4 Versus Raspberry Pi 5 With Hailo-8L

A real-time face tracking and detection system built using Raspberry Pi 5 with Hailo-8L AI acceleration, compared against Raspberry Pi 4 performance.

Originally published on ElectronicsForU

View original tutorial

Parts You'll Need

This project is sourced from another site, not written by us — this list is our best match of their components against what we stock, not a verified bill of materials. Always check the original blog (linked above) for the actual parts list before buying.

Raspberry Pi 3 - Model B+ 1.4Ghz 64-bit quad-core Processor with 1 GB Ram (Original) Rs. 5,400.00
TowerPro SG90 Mini Servo – 180 degree Rotation – Standard Quality Rs. 179.00
DC Motor Plastic Fan Blade Rs. 19.00
0.96 Inch I2C/IIC 4pin OLED Display Module White Rs. 349.00
400 Points Mini Solderless Prototype PCB Breadboard High Quality Rs. 89.00
MB102 Adjustable Breadboard Power Supply Module (3.3V & 5V) for Arduino & Raspberry Pi Rs. 139.00
Jumper Wire 10 Pin Male To Male 20cm Rs. 45.00
Jumper Wire 10 Pin Male To Female 20cm Rs. 45.00

Selected: Rs. 0.00

We don't carry yet: LCD (generic / unspecified)
Servo Driver (PCA9685)
Hailo-8L AI accelerator

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How It Works

This advanced edge AI project creates an interactive, real-time face tracking and detection system powered by a Raspberry Pi 5 enhanced with a Hailo-8L AI accelerator, and compares its processing capabilities against a Raspberry Pi 4 Model B. At the core of the computer vision pipeline is a high-resolution Raspberry Pi camera that continuously captures video frames of the surrounding environment. These frames are processed using Python, OpenCV, and YOLO models running inference either on the Pi's native hardware or accelerated via the Hailo-8L module. When a face is detected within the frame, the system calculates spatial coordinates to determine the subject's position relative to the camera's center view. To keep the face centered, the central processing board communicates control commands over the I2C protocol to a PCA-9685 servo driver board. The PCA-9685 generates precise Pulse Width Modulation (PWM) signals to drive two micro gear servo motors, which physically pan and tilt the camera platform to follow the movement. Operational metrics and system data can be monitored in real-time via an attached HDMI display and a smaller OLED display. Power is stably delivered to the system using a dedicated 5V 3A Raspberry Pi power adaptor, while a specialized heat sink and active cooling fan manage the substantial thermal output generated by continuous high-performance neural network workloads on both the mainboard and the AI accelerator.

Why Build This

Benchmark edge computing performance by directly comparing the neural processing capabilities of a Raspberry Pi 4 versus a Raspberry Pi 5 equipped with a dedicated Hailo-8L AI accelerator.

Develop real-world interactive robotics applications capable of autonomous computer vision tracking, dynamic mechanical panning, and tilt control.

Implement advanced software frameworks like TensorFlow Lite, OpenCV, and YOLO object detection models within a resource-constrained embedded Linux environment.

Real-World Application

Interactive robotics, surveillance systems, automation, and computer vision research.

Skills You'll Learn

Neural network inference optimization

Computer vision pipeline integration

PWM servo motor control

I2C bus communication

Thermal management for embedded systems

Hardware performance benchmarking

Safety Precautions

Ensure proper thermal management and cooling (heatsinks and fans) for the Raspberry Pi 5 and Hailo-8L accelerator during intensive AI workloads to prevent overheating.

Technology Tags

MACHINE LEARNING

COMPUTER VISION

RASPBERRY PI

HAILO-8L

OPENCV

TENSORFLOW LITE

YOLO

SERVO MOTOR

FACE TRACKING

Frequently Asked Questions

Why is a dedicated Hailo-8L AI accelerator used alongside the Raspberry Pi 5?

The Hailo-8L offloads heavy neural network computations from the main CPU, allowing the system to run complex YOLO vision models at significantly higher frame rates compared to a standard Raspberry Pi 4 or an unaccelerated Pi 5.

Can I power the micro gear servo motors directly from the Raspberry Pi 5 5V pin?

It is strongly recommended to power the servos through the PCA-9685 servo driver using an independent power source rather than drawing heavy current directly from the Raspberry Pi pins, though the system uses a robust 5V 3A adaptor for the mainboard.

What is the role of the PCA-9685 board in this tracking setup?

The PCA-9685 is an I2C-controlled 16-channel PWM driver that relieves the Raspberry Pi of the precise timing demands required to drive multiple servo motors smoothly for the pan-and-tilt mechanism.

Gallery

This page is part of Kitkraft's Project Hub — a curated collection of electronics & robotics projects gathered from the maker community to help students and hobbyists discover and learn to build. Kitkraft does not claim authorship of the original project, and makes no representation as to the accuracy, completeness or safety of third-party source material. The summary and "How It Works" explanation above are AI-generated, rewritten with reference to the original tutorial — not a reproduction of it. Full credit and a direct link to the original source are provided above. If you're the original creator and have a concern about how your work is represented here, please contact us and we'll address it promptly.

Kitkraft Project Hub — curated from the maker community, credited at the source.

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