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
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++：https://github.com/ajdroid/facetrackerapp
10. kylemcdonald/FaceTracker：https://github.com/kylemcdonald/FaceTracker
11. http://note.youdao.com/groupshare/web/file.html?token=4F58BCBC04714A7C8ADE604364BA97BB&gid=22052122
12: ofxFaceTracker:https://github.com/kylemcdonald/ofxFaceTracker
参考链接：http://www.learnopencv.com/facial-landmark-detection/#comment-2471797375