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An MTCNN based face detection and an optical-flow based tracking running in two threads.

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zlingkang/mtcnn_face_detection_and_tracking

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mtcnn_face_detection_and_tracking

An MTCNN based face detection and an optical-flow based tracking running in two threads.

face detection

An MTCNN based face detector modified from https://github.com/deepinsight/mtcnn-ncnn
Its implementation is based on the deeplearning platform ncnn

tracking

An optical-flow and Kalman Filter based multiple object tracker, more details: https://github.com/zlingkang/multi_object_tracker

Usage

  • Compile ncnn
    go to 3rd_party/mtcnn-ncnn/ and
    mkdir build
    cd build
    cmake ..
    make

  • Compile mtcnn face detector
    go to 3rd_party/mtcnn-ncnn/mtcnn/ and mkdir build
    cd build
    cmake ..
    make

  • Compile the tracker
    in the repo root directory, modify the OpenCV path in CMakeLists.txt and
    mkdir build
    cd build
    cmake ..
    make

  • Run
    go to build/ and
    ./multi_thread_det_and_track
    make sure USB camera is plugged in, otherwise if reading from video, modify main.cpp line 10 and 27.

Other notice

  • Running on embedded platform (Raspberry Pi, Odroid ...)
    When compiling ncnn, in 3rd_party/mtcnn-ncnn/src/, copy CMakeLists_arm.txt to CMakeLists.txt,
    and add add_definitions(-mfpu=neon) in 3rd_party/mtcnn-ncnn/CMakeLists.txt.
    This will make the face detection much faster.
  • Tune tracker's parameters
    checkout https://github.com/zlingkang/multi_object_tracker

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An MTCNN based face detection and an optical-flow based tracking running in two threads.

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