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A Keras + Theano implementation of my CVPR 2017 paper "POSEidon: Face-from-Depth for Driver Pose Estimation"

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POSEidon: Face-from-Depth for Driver Pose Estimation

Implementation in Keras and Theano of my paper published in CVPR 2017 (Borghi G., Venturelli M., Vezzani R., Cucchiara R.).

How To

Configuration

The model has been tested with the following configuration:

  • Python 2.7
  • OpenCV 2.4.11
  • Keras 1.0.6
  • Theano

Dataset (Biwi)

In order to run the code, it is necessary download the dataset from here and following these steps:

  • Create a folder for each run of each subject, naming from the number 01 to 24
  • In each sub folder, a file named angles.txt is required, where the first column is the frame number, then the roll, pitch and yaw angles.

It is necessary create the Motion Images (through the Farnerback algorithm) and the reconstructed grey images from the corresponding depth ones. In the Dataset directory you can find one test sequence with these types of data. We plan to release the complete dataset in the next future.

Train and Test

The command to train the network is

python3 train.py

and to test is

python3 test.py

and finally plot_error to plot the error and some graph. For both, you must pass the following arguments:

  • cpu or gpu0...gpun to run the script on cpu or on the n-th gpu
  • 1...n quantity of memory allocated in gpu device

Results

Input cropping is done using the ground truth head position.

Pitch Roll Yaw Avg
1.6 +/- 1.7 1.8 +/- 1.8 1.7 +/- 1.5 1.7 +/- 1.7

Note

Keras version

If you do not use Keras 1.0.6, scripts will run but thay will not produce the same reults reported in the original paper.

Path

In the code are present some hardcoded paths, at the beginning of train and test scripts.

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A Keras + Theano implementation of my CVPR 2017 paper "POSEidon: Face-from-Depth for Driver Pose Estimation"

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