RECBOT: Experiments on Face detection and recognition

Uses HAR cascades for fast good-enough face detection. Uses SFace for face recognition via cosine similarity against model computed features of samples.

Remember:

• Face Detection: is there a face in the image?
• Face Recognition: whose face is in the image?

Dependencies

• Install/Compile libopencv-dev and opencv-data
• Install cmake, make, and g++

Will use -march=native in order to enable SSE, AVX, et al. where possible.

Using

• make prepare will prepare cmake directories and download model and it's LICENSE.
• make build will build everything
• make sample will run the sampler to capture 10 samples of a face using the computer camera and crop it to the bounding box found by the face detector.
• make recon will run the recognizer and output "PASS" or "FAIL", with exit codes 0 or -1 respectively.

Binaries can be found on _build/.

Notes:

Choosing the camera

You can change the camera by changing the index (0) on: #define CAMERA_INDEX 0 in both recbot_recon.cpp and recbot_samples.cpp. Use ls /dev/video* to list, and note that not all devices are actual cameras.

Simple Detection Example

Under ./examples/ you can check a simple face detection example using HAR Cascades.

Troubleshooting:

If vscode intellisense is not working add "/usr/include/**" or equivalent to includePath in the C/C++ properties (c_cpp_properties.json).

TODO:

• Command line argument parsing
• Make this work with PAM for authentication
• Ensure memory is not leaking, because right now this runs as a one shot POC and I didn't care.