去年在美图公司实习的时候，研究了一段时间的SDM方法，写了一系列的博客，见《Supervised Descent Method and its Applications to Face Alignment》等，今年来到了杭州，进入了图片社交领域的佼佼者in实习，主要还是做人脸对齐。最近一段时间，一直在研究《Face Alignment at 3000 FPS via Regressing Local Binary Features》这篇文章，也为此搜集了很多资料，特整理在此，以供参考。
paper:
3000fps论文链接:
Face Alignment at 3000 FPS via Regressing Local Binary Features
SDM论文链接:
Supervised Descent Method and its Applications to Face Alignment
Supervised Descent Method for Solving Nonlinear Least Squares Problems in Computer Vision
github code linking:
3000fps:
- luoyetx/face-alignment-at-3000fps(C++)
- freesouls/face-alignment-at-3000fps(C++)
- yulequan/face-alignment-in-3000fps(C++)
- jwyang/face-alignment(matlab)
- jwyang/face alignment in 3000fps with C++
- soundsilence/FaceAlignment
SDM:
- patrikhuber/superviseddescent(C++11)
- patrikhuber/superviseddescent说明
- IntraFace(SDM官网)
- SDM作者主页
- IntraFace说明
- tntrung/impSDM(matlab)
- IntraFace 官方给的代码，可直接运行
other linking
- Face Alignment 最近几年paper收集
- An Empirical Study of Recent Face Alignment Methods
- Heng Yang @ Cambridge
- flandmark : Open-source implementation of facial landmark detector
- Supervised Descent Method Face Alignment 代码下载和算法研究
- 浅谈随机森林在人脸对齐上的应用~
- Face Alignment at 3000 FPS via Regressing Local Binary Features(luoyetx’blog)
- Face alignment at 3000FPS via Regressing Local Binrary features 理解
- C++实现和解读Face Alignment at 3000fps via Local Binary Feature
- SDM ppt
- 3000fps ppt
- Face Alignment at 3000FPS（C++版）工程配置
- Face Alignment at 3000FPS(matlab)工程配置
开源库链接及评价
评价：速度快，可商用，有些时候不太准确
2. CLM-framework: https://github.com/TadasBaltrusaitis/CLM-framework，
新版已经改为OpenFace，见：https://github.com/TadasBaltrusaitis/OpenFace
评价:很准确，不可商用
3. Face Detection, Pose Estimation and Landmark Localization in the Wild :http://www.ics.uci.edu/~xzhu/face/
评价:Very slow (~10 seconds an image after hyper threading on a 8-core CPU), but very accurate when it comes to high pose variations
4. SDM patrikhuber/superviseddescent:https://github.com/patrikhuber/superviseddescent
评价:Nicely written C++ code, though not very robust
5. Robust face landmark estimation under occlusion：http://www.vision.caltech.edu/xpburgos/ICCV13/
评价:Specially designed for handling occlusions(遮挡区域), but slow on account being written in MATLAB.
6. 应用了CLM的项目：https://www.technologyreview.com/s/541866/this-car-knows-your-next-misstep-before-you-make-it/
评价:I actually explored a large number of open-source facial landmark detectors for a project, and found the CLM framework to outperform everything else (in terms of both speed and accuracy). We eventually used it in our project: www.technologyreview.com/news/…
7. clandmark：https://github.com/uricamic/clandmark
8. kylemcdonald/FaceTracker：https://github.com/kylemcdonald/FaceTracker
9. Android app for facial landmark tracking
评价：安装该app需要OpenCV Manager，我已提供链接.。
至于效果，不是很好，需要优化。不过上面提供了编写jni的代码，对于编写C++的API应该会有帮助。
10. kylemcdonald/FaceTracker：https://github.com/kylemcdonald/FaceTracker
11. ofxFaceTracker:https://github.com/kylemcdonald/ofxFaceTracker
