Neurotechnology launches SentiMask SDK

Neurotechnology has introduced the SentiMask SDK for real-time face tracking and masking, 3D digital character control and other applications.

According to a company statement, the SentiMask algorithm can detect and track the user’s face, in real time from a regular video stream, such as a webcam, or in a video file, and it does not require depth sensors or any other special hardware.

The output from SentiMask is in the form of 2D and 3D coordinates that represent certain facial feature points. These landmarks can be used to construct a face mesh and various textures can be applied onto that mesh. When used as an animated avatar or mask, for example, the mesh and textures respond to, and move with, the user’s facial expressions.

“Our decades of experience in biometric facial recognition has enabled us to create our new SentiMask SDK product, which uses our latest facial image processing technologies in a non-biometric way,” explained Dr. Vilius Matiukas, SentiMask project lead for Neurotechnology. “With SentiMask, our customers can easily incorporate face detection and tracking capabilities into their own solutions, such as entertainment or interactive marketing applications.”

SentiMask SDK features include: real-time face detection and tracking; 2D & 3D facial landmark estimation; 3D facial pose, shape and expression estimation; 3D facial mesh output, and; facial expression analysis.

SentiMask SDK supports development environments under Windows and Linux PC platforms and the mobile Android platform.

Earlier this year, Neurotechnology released SentiVeillance 6.0 SDK, which provides improved facial recognition using up to 10 surveillance, security and public safety cameras on a single computer, making it suitable for a wide range of surveillance applications.

Article Topics

 |   |   | 

Comments

Leave a Reply

This site uses Akismet to reduce spam. Learn how your comment data is processed.

Most Read This Week

Biometrics Research Group

Biometrics White Papers

Biometrics Events

Explaining Biometrics