Detect Hand Pose with Vision

What if your app could track 21 distinct hand joints in real time? Learn to build powerful gesture-based controls using Apple's Vision framework.

#1about 2 minutes

Understanding the capabilities of Apple's Vision framework

The Vision framework provides out-of-the-box machine learning tools for image analysis, including object detection, image classification, and tracking faces.

#2about 3 minutes

Recognizing 21 distinct hand landmarks with Vision

Vision processes hand poses by identifying 21 specific landmarks, including the wrist, palm, and four points on each finger and thumb.

#3about 1 minute

Common issues and limitations in hand pose detection

Hand pose recognition can fail due to common real-world issues like partial occlusion, hands near screen edges, wearing gloves, or confusing hands with feet.

#4about 4 minutes

Exploring the structure of the hand tracking Xcode project

The sample application is built around three main components: a CameraView for display, a ViewController for control logic, and a HandGestureProcessor for analyzing gestures.

#5about 2 minutes

Live demo of a drawing app using pinch gestures

A live demonstration shows how to use the tips of the thumb and index finger to create a pinch gesture that draws lines on the iPhone screen.

#6about 4 minutes

Key classes and properties for implementing hand tracking

The implementation relies on key classes like CameraViewController, VNdetectHumanHandPoseRequest for analysis, and UIBezierPath for drawing the visual feedback.

#7about 5 minutes

Processing hand pose observations from the Vision framework

The VNImageRequestHandler processes the camera buffer and returns observations, from which you can extract the coordinates of specific finger joints like the thumb tip.

#8about 2 minutes

Implementing gesture state logic for pinch detection

A custom processor manages gesture states like 'pinched' or 'apart' by calculating the distance between finger landmarks and using a counter for stability.

#9about 1 minute

Applying similar techniques for human body pose detection

The same principles used for hand pose can be applied to full-body pose detection, which tracks major body joints like shoulders, eyes, and ears.

#10about 3 minutes

Exploring potential applications for pose detection

Pose detection technology can be used to build applications that understand sign language, analyze human interaction in images, or create new forms of user input.