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.
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
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.
FDDB: http://vis-www.cs.umass.edu/fddb/index.html
- 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.
- Shiqi Yu, [email protected]
- Jia Wu
- Shengyin Wu
- Dong Xu
- The result image was taken by Chloé Calmon.