2022-02-10 visage|SDK 8.8.1
Platform: Android
- Lowered minimum supported API level to 21 (Android 5.0)
Platform: Android
Platforms: all
Liveness API exposure
The usage of the Liveness preset actions is now also available through the FaceRecognition license.
Upgrade of VNN algorithm for tracking and detecting masked faces
Face tracking and detection algorithms are enhanced so that they can track and detect faces wearing protective masks of various colors and patterns.
Removal of the legacy tracking and detection algorithm
With the improvement of the quality and performance of the VNN algorithm, we have achieved state-of-the-art face tracking and detection. In order to simplify usage and reduce the data, all those algorithms that are no longer competitive are removed.
Switching from visible to physical contour
Introducing the physical contour the stability and accuracy of one of the main visage|SDK features – 3D head-pose estimation has been improved. Improved the usability of the visage|SDK for many market fields such as DMS, Virtual Try-on, and Gaming.
Swift wrapper
It is now possible to develop with the visage|SDK in Swift language on iOS and macOS using the newly implemented Swift wrapper
Platforms: Linux
The initial release of visage|SDK for the in-cabin use case optimized for face tracking on near-infrared images.
Platforms: all
Face tracking and detection algorithms are enhanced so that they can track and detect faces wearing protective masks of various colors and patterns.
Introducing the physical contour the stability and accuracy of one of the main visage|SDK features – 3D head-pose estimation has been improved. Improved the usability of the visage|SDK for many market fields such as DMS, Virtual Try-on, and Gaming.
Platform: iOS
You can now develop with visage|SDK using Swift language on iOS using a newly implemented Swift wrapper
Platform: Ambarella
The initial release of visage|SDK for Ambarella. Offers single-face FaceTrack functionality.
Platform: HTML5
Platform: Linux, RedHat
Introducing a smaller, faster, and more accurate face recognition model.
Introducing improved face detection model, more robust to various challenging conditions such as faces with high variability in scale, illumination, pose and occlusion.
Introducing new VNN algorithm fast mode which significantly improves performance at the cost of feature points precision while keeping the same precision of head pose.
VNN tracking algorithm now works with higher FPS, with significant improvements on devices such as high-end mobile and desktop devices.
New VNN tracking models now work with less tracking jitter.
Introducing improved face detection model, more robust to various challenging conditions such as faces with high variability in scale, illumination, pose and occlusion.
Introducing new VNN algorithm fast mode which significantly improves performance at the cost of feature points precision while keeping the same precision of head pose.
VNN tracking algorithm now works with higher FPS, with significant improvements on devices such as high-end mobile and desktop devices
New VNN tracking models now work with less tracking jitter.
Introducing new runner – TensorFlow Lite, optimized for running neural networks and significantly improving the performance of visage|SDK algorithms.
Introducing a smaller, faster, and more accurate face recognition model that completely replaces the old model that will no longer be distributed.
The model is available for OpenVino™ runner on desktop platforms and Tensorflow Lite runner on mobile platforms.
The new algorithm minimizes jitter, increases tracking accuracy and robustness but reduces tracking performance (speed). It is demonstrated in ShowcaseDemo and FaceTracker2 samples via Ultra tracking configuration.
Significantly improves the performance of age estimation, face recognition and face tracking with VNN algorithm on Intel 64-bit processors.
Additional 24 feature points on ears are now tracked (12 points per ear). Ear tracking is configurable through the tracker configuration file or API.
Face data from tracker and detector now includes information about iris diameter.
It is now possible to modify specific tracker configuration parameters via an interface during tracking.
Platform: HTML
Platforms: iOS, Android