Description

Features:
– You can detect frontal human faces and face landmark (68 points, 17points, 6points) in Texture2D, WebCamTexture and Image byte array. In addition, You can detect a different objects by changing trained data file.

– ObjectDetector is made using the now classic Histogram of Oriented Gradients (HOG) feature combined with a linear classifier, an image pyramid, and sliding window detection scheme. You can train your own detector in addition to human faces detector. If you want to train your own detector, please refer to this page.

– ShapePredictor is created by using dlib’s implementation of the paper(One Millisecond Face Alignment with an Ensemble of Regression Trees by Vahid Kazemi and Josephine Sullivan, CVPR 2014). You can train your own models in addition to human face landmark model using dlib’s machine learning tools. If you want to train your own models, please refer to this page.

– Advanced examples using “OpenCV for Unity” are Included. (The execution of this examples are required “OpenCV for Unity”.)

– PlayMakerActions for DlibFaceLandmarkDetector is available.

Examples:
Texture2DExample
WebCamTextureExample
CatDetectionExample

Advanced Examples:
(require OpenCV for Unity)
Texture2DToMatExample
WebCamTextureToMatHelperExample
VideoCaptureExample
ARHeadWebCamTextureExample
VideoCaptureARHeadExample
FrameOptimizationExample
NoiseFilterWebCamTextureExample
NoiseFilterVideoCaptureExample

DlibFaceLandmarkDetector uses Dlib under Boost Software License ; see Third-Party Notices.txt file in package for details.
The Shape Predictor model files included with this asset are available for commercial use.

System Requirements
Build Win Standalone & Preview Editor : Windows 8 or later
Build Mac Standalone & Preview Editor : OSX 10.9 or later
Build Linux Standalone & Preview Editor : Ubuntu16.04 or later