Luxand FaceSDK 7.2.1 [Latest]

Luxand FaceSDK – is a useful program that is used in hundreds of applications for identifying and authenticating users with webcams, looking up matching faces in photo databases, automatically detecting facial features in graphic editors, and detecting faces on still images and video streams in real-time. FaceSDK has been used for building secure identification, surveillance, time and attendance control systems.

Luxand’s patent pending technology detects facial features quickly and reliably. The SDK processes an image, detects human faces within it, and returns the coordinates of 70 facial feature points including eyes, eye contours, eyebrows, lip contours, nose tip, and so on.

The SDK automates the task, allowing you to make new avatars on the fly. Imagine letting your customers upload their pictures and immediately receive their animated avatars! The SDK recognizes the face in a photograph and returns the coordinates of facial features in a list of anchor points. Your software can easily match facial features such as eyes, mouth, nose, and ears to the points on your 3D head model, creating a head that looks and moves like the original.

Features
• Detect Human Faces and Facial Features
• Immerse Yourself in Augmented Reality
• Create 3D Head Models
• Make Animated 3D Avatars Completely Automatically

What’s New
* We have just released FaceSDK version 7.2.1 that adds the support of Apple Silicon processors (arm64) in MacOS, to follow the latest Apple’s announcement of Mac computer transition to new arm64-based processors.
* We have also added a Mask-on Face Detection model – it’s now possible to detect faces covered by masks (medicine masks, scarfs, bandanas, etc), which significantly improves face detection quality during pandemics.
* In addition to a few major updates above we have also fixed problems with merging Tracker databases in trackerMemoryTool.py.

Title Release: Luxand.FaceSDK.7.2.1
Developer: Home Page
License: ShareWare
OS: Windows
Download:
Luxand FaceSDK 7.2.1 (578 MB)