This JavaScript library detects and tracks the face in real time from the webcam video feed captured with WebRTC. Then it is possible to overlay 3D content for augmented reality applications. We provide various demonstrations using main WebGL 3D engines. We have included in this repository the release versions of the 3D engines to work with a determined version (they are in /libs/
Tags | face tracking detection snapchat 3d webgl deep-learning face-detection face-tracking threejs babylonjs webcam faceswap library picojs augmented-reality face-filters trackingjs msqrd |
Implementation | Javascript |
License | Apache |
Platform | OS-Independent |
With this library, you can build your own animoji embedded in Javascript/WebGL applications. You do not need any specific device except a standard webcam. By default a webcam feedback image is displayed with the face detection frame. The face detection is quite robust to all lighting conditions, but the evaluation of expression can be noisy if the lighting is too directional, too weak or if there is an important backlight. So the webcam feedback image is useful to see the quality of the input video feed.
webgl threejs svg animoji weboji webcam deep-learning face face-expression computer-vision augmented-reality emoji face-detection face-tracking real-timeThis is a demo app showing face tracking and 3D Morphable Model fitting on live webcams and videos. It builds upon the 3D face model library eos and the landmark detection and optimisation library superviseddescent. Clone with submodules: git clone --recursive git://github.com/patrikhuber/4dface.git, or, if you've already cloned it, get the submodules with git submodule update --init --recursive inside the 4dface directory.
computer-vision face-models video-processing modern-cppPigo is a pure Go face detection library based on Pixel Intensity Comparison-based Object detection paper. The only existing solution for face detection in the Go ecosystem is using bindings to OpenCV, but installing OpenCV on various platforms is sometimes daunting. This library does not require any third party modules to be installed. However in case you wish to try the real time, webcam based face detection you might need to have Python2 and OpenCV installed, but the core API does not require any third party module or external dependency.
face detection decision trees face-detection eyes facial-landmarkIt is a real time face detection and tracking SDK. You put in image data (camera stream or single picture) and it outputs facial data. This page also includes all available packages for download.
face tracking detection emscripten web face-tracking face-detectionThe folder img/ contains a demo that shows how to detect faces in still images. The folder cam/ shows how to do webcam-based real-time face detection. Use these files as documentation. The folder wasm/ demonstrates how to compile pico to WebAssembly.
Detect facial landmarks from Python using the world's most accurate face alignment network, capable of detecting points in both 2D and 3D coordinates. Build using FAN's state-of-the-art deep learning based face alignment method. For detecting faces the library makes use of dlib library.
deep-learning face-alignment face-detector pytorchSimple Node.js API for robust face detection and face recognition. This a Node.js wrapper library for the face detection and face recognition tools implemented in dlib. Installing the package will build dlib for you and download the models. Note, this might take some time.
face-detection face-recognition face nodejs node face-landmark typescript detection recognitionFace detector is a face detection Android library which can be easily plugged into any camera API (given it provides a way to process its frames). Face detector is built on top of Firebase ML Kit's face detection API.
android kotlin face-detection firebase-mlkitThis is a TensorFlow implementation of the face recognizer described in the paper "FaceNet: A Unified Embedding for Face Recognition and Clustering". The project also uses ideas from the paper "Deep Face Recognition" from the Visual Geometry Group at Oxford. The code is tested using Tensorflow r1.7 under Ubuntu 14.04 with Python 2.7 and Python 3.5. The test cases can be found here and the results can be found here.
face-recognition tensorflow facenet deep-learning computer-vision face-detection mtcnn neural-networksSphereFace is released under the MIT License (refer to the LICENSE file for details). 2018.8.14: We recommand an interesting ECCV 2018 paper that comprehensively evaluates SphereFace (A-Softmax) on current widely used face datasets and their proposed noise-controlled IMDb-Face dataset. Interested users can try to train SphereFace on their IMDb-Face dataset. Take a look here.
face-recognition caffe sphereface cvpr-2017 face-detection angular-softmax deep-learningA "syllabus" and repository of Processing examples for ITP fall workshop about face detection, recognition, and miscellaneous tracking methods.
Recognize and manipulate faces from Python or from the command line with the world's simplest face recognition library. Built using dlib's state-of-the-art face recognition built with deep learning. The model has an accuracy of 99.38% on the Labeled Faces in the Wild benchmark.
machine-learning face-detection face-recognitionFree and open source face recognition with deep neural networks. This research was supported by the National Science Foundation (NSF) under grant number CNS-1518865. Additional support was provided by the Intel Corporation, Google, Vodafone, NVIDIA, and the Conklin Kistler family fund. Any opinions, findings, conclusions or recommendations expressed in this material are those of the authors and should not be attributed to their employers or funding sources.
deep-learning face-recognition facenet face-detection neural-networksThe Accord.NET project provides machine learning, statistics, artificial intelligence, computer vision and image processing methods to .NET. It can be used on Microsoft Windows, Xamarin, Unity3D, Windows Store applications, Linux or mobile.
machine-learning framework c-sharp nuget visual-studio statistics unity3d neural-network support-vector-machines computer-vision image-processing ffmpegLibface is a cross platform framework for developing face recognition algorithms and testing its performance. The library uses OpenCV 2.0 and aims to be a middleware for developers that don’t have to include any OpenCV code in order to use face recognition and face detection detection.
face-detection image-recognization image image-processingJavaScript API for face detection and face recognition in the browser with tensorflow.js
face-recognition face js tensorflow tfjs neural-network resnet-34 convolutional-neural-networks face-detection face-similarity ssd-mobilenet face-landmarks mtcnn yolov2 tiny-yolo detection recognition tfStarTrinity.com face detection project makes it easier for Silverlight, .NET, Windows Phone 7 developers to detect faces from any image. Facial tracking algorithm is based on Haar features and adaboost training. It is developed in C#
face-detectionThe tracking.js library brings different computer vision algorithms and techniques into the browser environment. By using modern HTML5 specifications, we enable you to do real-time color tracking, face detection and much more — all that with a lightweight core (~7 KB) and intuitive interface. You can plug tracking.js into some well supported HTML elements such as <canvas>, <video> and <img>.
tracking trackingjs webrtcApplication project using the Face SDK for Windows Phone for demonstration purpose
face-detection face-sdk live-tracking microsoft-research windows-phoneSOD is an embedded, modern cross-platform computer vision and machine learning software library that expose a set of APIs for deep-learning, advanced media analysis & processing including real-time, multi-class object detection and model training on embedded systems with limited computational resource and IoT devices. SOD was built to provide a common infrastructure for computer vision applications and to accelerate the use of machine perception in open source as well commercial products.
computer-vision library deep-learning image-processing object-detection cpu real-time convolutional-neural-networks recurrent-neural-networks face-detection facial-landmarks machine-learning-algorithms image-recognition image-analysis vision-framework embedded detection iot-device iot
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