很高興今日(2021/2/25)受邀在「Edge AI 社聚」和大家分享關於邊緣智能上人臉辨識相關技術。此次從傳統算法介紹到目前人工智慧算法,並分別解釋相關辨識基準,主要包括下列項目,希望能幫助大家能快速進入「人臉辨識」這個領域
- 人臉辨識應用
- 人臉辨識技術
- 人臉辨識發展
- 人臉資料集
- 人臉辨識基準
- 開源辨識工具
人臉特徵點資料集:
MTFL, 12,955 images with 5 landmarks
http://mmlab.ie.cuhk.edu.hk/projects/TCDCN.html
FRGC-V2, with 5 landmarks
https://www.nist.gov/programs-projects/face-recognition-grand-challenge-frgc
AFW, 205 images with 6 landmarks
https://www.cs.cmu.edu/~deva/papers/face/
BioID Face, 1,521 images with 20 landmarks
https://www.bioid.com/facedb/
AFLW, 25,933 images with 21 landmarks
https://www.tugraz.at/institute/icg/research/team-bischof/lrs/downloads/aflw/
COFW, 1,345 images with 29 landmarks
http://www.vision.caltech.edu/xpburgos/ICCV13/
LFPW, 1,432 images with 35 landmarks
https://neerajkumar.org/databases/lfpw/
BUHMAP-DB, 440 videos with 52 landmarks
https://www.cmpe.boun.edu.tr/pilab/pilabfiles/databases/buhmap/
XM2VTS, 2,360 images with 68 landmarks
https://personalpages.manchester.ac.uk/staff/timothy.f.cootes/data/xm2vts/xm2vts_markup.html
300W, 3,837 images with 68 landmarks
https://ibug.doc.ic.ac.uk/resources/300-W/
MUCT, 3755 images with 76 landmarks
http://www.milbo.org/muct/
WFLW, 10,000 images with 98 landmarks
https://wywu.github.io/projects/LAB/WFLW.html
ICME, 16,000 images with 106 landmarks
https://facial-landmarks-localization-challenge.github.io/#introduction
HELEN, 2,330 images with 194 landmarks
http://www.ifp.illinois.edu/~vuongle2/helen/
參考文獻
National Institute of Standards and Technology (NIST), Face Recognition Vendor Test (FRVT) Ongoing
https://www.nist.gov/programs-projects/face-recognition-vendor-test-frvt-ongoing
許哲豪,【開箱測試】研華科技AI人臉辨識運算智能系統
http://omnixri.blogspot.com/2020/12/ai.html
OpenCV Tutorials for face module (4.0.0)
https://docs.opencv.org/4.0.0/de/d27/tutorial_table_of_content_face.html
Overview of OpenVINO™ Toolkit Intel's Pre-Trained Models
https://docs.openvinotoolkit.org/latest/omz_models_intel_index.html
Overview of OpenVINO™ Toolkit Public Models
https://docs.openvinotoolkit.org/latest/omz_models_public_index.html
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