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Abstract

Facial expression recognition has been an active research topic for many years. In this paper a method for automatically recognizing pain intensity in images with facial expressions will be implemented. The method presented will contain a first step in which the face and the important points on the face will be located using the DLIB library. The second step consists of the calculation of HOG-type traits in order to describe the face found. The traits will be used to train a Random Forest (RF) regressor that will estimate the intensity of the pain. Training and testing will be done on the public UNBC-McMaster shoulder Pain Expression Archive database, using Python programming.

Keywords

Image processing Facial recognition HOG(Histogram of oriented Gradients) Random Forest DLIB 

Notes

Acknowledgment

This work has been supported in part by UEFISCDI Romania and MCI through projects VIRTUOSE, EmoSpaces and PAPUD, funded in part by European Union’s Horizon 2020 research and innovation program under grant agreement No. 777996 (SealedGRID) and No. 787002 (SAFECARE).

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Copyright information

© ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2019

Authors and Affiliations

  1. 1.Faculty of Electronics, Telecommunications and Information TechnologyUniversity Politehnica of BucharestBucharestRomania
  2. 2.R&D Department BEIA Consult InternationalBucharestRomania

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