edmig / 3d-facial-landmark-detection-and-tracking

Human 3D Facial Pose Estimation and Tracking (AffCom IJCAI2018)

Landmark Detection and Tracking

We use two open source library in our project. You need to download and install them before running our scripts. One is Dlib (See http://dlib.net for downloading and installation). Another one is eos, which is a lightweight 3D Morphable Face Model fitting library.(The link is https://github.com/patrikhuber/eos/releases.)

Sample code

Run the code “landmark_detection_img.py”. It will show the landmark detection of a sample image. As for video processing, “landmark_detection_video.py” shows the landmark tracking in a sample video.

Citation

If you find our work useful in your research please consider citing our paper:

@INPROCEEDINGS{facial2018yin,

title = {Facial Expression and Peripheral Physiology Fusion to Decode Individualized Affective Experience},
author = {Yin, Y and Nabian, M and Fan, M and Chou, C and Gendron, M and Ostadabbas, S},
booktitle = {2nd Affective Computing Workshop of the 27th International Joint Conference on Artificial Intelligence (IJCAI)},
year = {2018}

}

For further inquiry please contact:

Sarah Ostadabbas, PhD Electrical & Computer Engineering Department Northeastern University, Boston, MA 02115 Office Phone: [phone] [email protected] Augmented Cognition Lab (ACLab) Webpage: http://www.northeastern.edu/ostadabbas/