What is the connection between facial recognition and USB cameras?

USB Camera: Responsible for "seeing"—capturing real-time images and facial images/video streams, converting optical images into digital data, and transmitting it to a computer/device via USB.

Facial Recognition Algorithm: Responsible for "recognizing"—reading the image from the camera, locating the face, extracting features, comparing identities, and completing the recognition.

✅ In short: Without a USB camera capturing images, the facial recognition algorithm has no data to analyze and cannot function.

Plug and Play: No disassembly required; simply plug it into a computer, industrial PC, or all-in-one machine; compatible with Windows/Linux.

Low Cost and High Versatility: Access control, attendance systems, turnstiles, and desktop facial login mostly use ordinary USB camera modules.

Convenient Data Transfer: Video streams are stably uploaded to the AI program via the USB protocol, with low latency, meeting real-time recognition requirements.

Not just any USB camera can perform face recognition:

Resolution: At least 720P/1080P. Low-resolution images result in blurred facial features and a high failure rate.

Backlight/Low-Light Imaging: Indoor low-light or backlight environments require wide dynamic range and night vision supplemental lighting; otherwise, faces will not be clearly captured.

Frame Rate: ≥30 frames per second. Image stuttering will cause unstable face recognition tracking.

No Distortion: Severe wide-angle distortion will distort facial contours, leading to inaccurate algorithm recognition.

Advanced Face Recognition (Payment/High-Security Access Control): Requires a dual-lens USB camera or an infrared USB camera.

Ordinary RGB USB Cameras: Only suitable for basic face check-in and login; easily impersonated by photos.

Infrared/Depth USB Cameras: Liveness detection, protection against photo and video attacks, and higher security.

1. USB camera powered on and plugged into device → 2. Driver recognition and video stream activation → 3. Face recognition software reads camera image → 4. Algorithm detects facial key points + liveness detection → 5. Compares with database, outputs "Recognition successful / failure"

Mobile phone face recognition: Uses built-in front-facing structured light/depth camera, not a USB interface;

Computer/Industrial control/Access control face recognition: Almost entirely relies on an external USB camera module combined with AI algorithms.