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Face tracking

As explained in Build Your Own Robot: Using Python, CRICKIT, and Raspberry Pi

Face tracking is the computer-vision technique of following a detected face across successive images or video frames.

Face tracking follows a detected face across camera frames and turns its position into physical movement. A live preview marks the face center and divides the image into left, center, and right zones. section 9.5.2

Face-following camera

Run follow.py on a Raspberry Pi with a camera and servo controller. Looking into the live feed shows a bordered face and crosshair; moving left or right causes the camera servo to re-center the face. section 9.5.2

How Build Your Own Robot: Using Python, CRICKIT, and Raspberry Pi covers it

How deep it goes
Implements horizontal zone detection and bounded pan-servo control, without covering broader visual-feature algorithms.
Examples
Uses a live face-marked preview, zoned movement, and the follow.py face-following camera application.
What it assumes
Assumes Python, OpenCV, a camera, and a Crickit-controlled servo, while providing the zone and movement logic.
What you can do after
Build it from scratch by connecting face detection to a camera servo that re-centers the detected face.
How it connects
Connects computer vision, machine learning, face detection, camera capture, and servo motors.
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