chili-epfl/ attention-tracker

C++

Python

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chili-epfl

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⚠️️ Attention: This library is currently not maintained. Please use the gazr fork instead. ⚠️️

Attention Tracker

Name: attention-tracker
Brand: attention-tracker
SKU: //chili-epfl/attention-tracker
Rating: 2.08 (132 reviews)

Head pose estimation

This library (

libhead_pose_estimation.so

) performs 3D head pose estimation based on the fantastic dlib face detector and a bit of OpenCV's solvePnP magic (it uses adult male anthropometric data to match a real 3D head to the projected image).

The library returns a 4x4 transformation matrix.

It supports detection and tracking of multiple faces at the same time, and runs on-line, but it does not feature face identification.

Installation

Note: The library has only been tested on Linux. We can only provide limited support for other operating systems!

Pre-requisites

Dlib: You need to download and extract

Dlib

somewhere. This application has been tested with

dlib-18.16

OpenCV: You need to install OpenCV. If you're using Ubuntu, you could run:

sudo apt-get install libopencv-dev

Installation

The library uses a standard

CMake

workflow:

$ mkdir build && cd build
$ cmake -DDLIB_PATH= ..
$ make

Note that the first time you compile the project,

dlib

will compile as well. It takes a few minutes. This won't happen the next times.

To test the library, run:

./head_pose_test ../share/shape_predictor_68_face_landmarks.dat

You should get something very similar to the picture above.

Finally, to install the library:

$ make install

ROS support

The ROS wrapper provides a convenient node that exposes each detected face as a TF frame.

Enable the compilation of the ROS wrapper with:

cmake -DWITH_ROS=ON