The in-house developed runner is no longer available and is being replaced by OpenVINO™ toolkit, which is now the only and default neural network runner.

It is implemented in the following libraries:

• OVPlugin.dll,

• inference_engine.dll,

• MKLDNNPlugin.dll,

• mkl_tiny_tbb.dll,

• tbb.dll

• libmmd.dll,

• svml_dispmd.dll

OpenVINO is a trademark of Intel Corporation or its subsidiaries.

The old face recognition model is being replaced by a smaller, faster and more accurate face recognition model.

Introducing a more accurate and robust face detection model. The new model is used in face tracking and face detection when use_vnn configuration parameter is set to 1. Otherwise, the previous face detection model will be used.

VNN algorithm can now be configured for better performance, at the cost of feature points precision. This mode is enabled by setting use_vnn parameter in configuration file to 1.

Added support for multiple image format for extractDescriptor() and addDescriptor() methods.

use_vnn configuration parameter added to VisageFeaturesDetector configuration file FaceDetector.cfg(located in Samples/data/bdstdata) and set to value 1.

use_vnn configuration parameter values changed and additional value added:

As a consequence of improving algorithms, removing in-house developed runner, and improving VNN algorithm, there are certain changes in the data files.

VisageTrackerUnityPlugin

Function _grabFrame() captures RGB image, instead of BGR image.

VisageTrackerUnityDemo

The previously used BGRATex texture shader for applying captured frame image data was replaced with RGBATex texture shader (Tracker.cs script).

To improve the performance of our algorithms and to support a wider variety of neural network models, we are introducing a configurable framework for choosing between different neural network runners.

As a result, additional configuration file NeuralNet.cfg is now included in visage|SDK (located in Samples/data). This file allows the users to configure which runner will be used by visage|SDK. Users can choose between:

• Visage Technologies' runner developed in-house and

• OpenVINO™ toolkit.

For more information on the parameters of NeuralNet.cfg file see the API page.

OpenVINO is a trademark of Intel Corporation or its subsidiaries.

New experimental algorithm for face tracking and alignment introduced - VNN algorithm.

For the price of slightly reduced tracking speed/performance, it significantly improves tracking quality and robustness. VisageTracker and VisageFeaturesDetector can be configured to use VNN algorithm via configuration parameter - use_vnn.

Introducing new C++ and C# API for programmatically changing VisageTracker configuration parameters, including new additional classes and templates:

The aforementioned classes are used in conjunction with new VisageTracker methods:

FDP group 10 (ears) has been extended from 10 to 24 points (12 points per ear) as part of the ear tracking feature.

VisageTracker method stop has been deprecated from both APIs.

Prototype of method

void initializeLicenseManager(const char *licenseKeyFileName)

changed to

int initializeLicenseManager(const char *licenseKeyFileName)

FeaturePoint class and FDP class have additional property and functions, respectively to conform with the C++ API.

Two additional configuration files have been added. One for the ear tracking feature and one for the novel tracking algorithm.

• refine_ears parameter added, off (0) by default. Toggles the tracking and refinement of ear points (group 10) for VisageTracker and VisageFeaturesDetector.

• use_vnn parameter added, off (0) by default. Toggles usage of the new experimental algorithm for face tracking and alignment - VNN algorithm

A new model file has been added for ear tracking functionality - jk_300_wEars.wfm. The model contains an additional 334 polygons and its vertices are mapped to 14 new FDP points in group 10 (10.11 - 10.24).

New data files and model files for ear tracking added

New data folder and data files added for VNN algorithm in Samples/data/bdtsdata/NN/vnn

FacialAnimationUnityDemo sample application has been removed and will no longer be distributed.

VisageTrackerUnityDemo sample application is distributed as a Unity project, not as a prebuilt application.

Build and run instructions are provided in the VisageTrackerUnityDemo sample documentation.

• smoothing_factors parameter
  Due to the re-implementation of the smoothing algorithm in VisageTracker, default values and optimal ranges for this parameter have been changed in all configurations.

VisageRendering.cs:

Methods DisplayEmotion() and DisplayAgeGenderName() have changed the prototypes from:

public void DisplayEmotion(FaceData trackingData, float[] emotions, int width, int height,
                           bool face_recognition_mode=false)
public void DisplayAgeGenderName(FaceData trackingData, float age, int gender, string name, 
                                 int width, int height, int drawingOptions, 
                                 bool face_recognition_mode=false)

to:

public void DisplayEmotion(FaceData trackingData, float[] emotions, int width, int height, 
                           bool display_background = false)
public void DisplayAgeGenderName(FaceData trackingData, float age, int gender, string name, 
                                 int width, int height, bool display_background = true)