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A fast binary library for face detection and face landmark detection in images. The face detection speed can reach 1500FPS. You can use it free of charge with any purpose.

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libfacedetection

This is a binary library for face detection and face landmark detection in images. The 32-bit and 64-bit dll files are provided. To achieve better performance, the 64-bit dll is recommended.

examples/libfacedetect-example.cpp shows how to use the library.

Examples

Comparison on Windows

Method Time FPS Time FPS Time FPS Misc
Win32 Win32 X64 X64 X64 X64
Single-thread Single-thread Single-thread Single-thread Multi-thread Multi-thread
OpenCV -- -- -- -- 12.33ms 81.1 Yaw angle: -60 to 60 degrees
frontal 2.92ms 342.5 2.41ms 414.9 0.652ms 1533.1 Yaw angle: -60 to 60 degrees
frontal-surveillance 3.83ms 261.1 3.37ms 269.7 0.944ms 1059.8 Yaw angle: -70 to 70 degrees
multiview 7.12ms 140.4 5.81ms 172.1 1.597ms 626.4 Yaw angle: -90 to 90 degrees
multiview_reinforce 10.95ms 91.3 9.15ms 109.3 2.725ms 367.0 Yaw angle: -90 to 90 degrees
  • Face detection only, and no landmark detection included.
  • 640x480 image size (VGA), scale=1.2, minimal window size = 48.
  • Intel(R) Core(TM) i7-4770 CPU @ 3.4GHz.
  • OpenCV classifier file: haarcascade_frontalface_alt.xml

Comparison on ARM

Method Time FPS Misc
frontal 12.5ms 80.0 Yaw angle: -60 to 60 degrees
frontal-surveillance 15.7ms 63.7 Yaw angle: -70 to 70 degrees
multiview 27.8ms 36.0 Yaw angle: -90 to 90 degrees
multiview_reinforce 38.4ms 26.0 Yaw angle: -90 to 90 degrees
  • Face detection only, and no landmark detection included.
  • 640x480 image size (VGA), scale=1.2, minimal window size = 48
  • NVIDIA TK1 "4-Plus-1" 2.32GHz ARM quad-core Cortex-A15 CPU
  • Multi-core parallelization is disabled.
  • C programming language, and no SIMD instruction is used.

The dll cannot run on ARM. The library should be recompiled from source code for ARM compatibility. If you need the source code, a commercial license is needed.

Binary library for ARM

The binary evaluation library for ARM can be downloaded at https://github.com/OAID/YSQfastfd . The detection functions can only be called about 2000 times for evaluation.

Accuracy evaluation

FDDB: http://vis-www.cs.umass.edu/fddb/index.html

Evaluation on FDDB

  • scale=1.08
  • minimal window size = 16
  • the heights of the face rectangles are scaled to 1.2 to fit the ground truth data in FDDB.

Author

Contributors

  • Jia Wu
  • Shengyin Wu
  • Dong Xu

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A fast binary library for face detection and face landmark detection in images. The face detection speed can reach 1500FPS. You can use it free of charge with any purpose.

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