Authors:
Jan Hintz
;
Jacob Rühe
and
Ingo Siegert
Affiliation:
Mobile Dialog Systems, Otto-von-Guericke University, Magdeburg, Germany
Keyword(s):
Anonymization, Privacy, Face Recognition, Emotion Recognition, Human Recognition, Human-Machine-Interaction.
Abstract:
Seeking therapy often implies a major hurdle, especially when it comes to addressing personal problems that cause shame or are socially stigmatized. This is where the recent developments of remote therapy can help. To further reduce this barrier, it can be accommodating to carry out the therapy anonymously. This paper present a proof of concept for such an anonymization of remote therapy video calls. The aim is to enable video calls for subjects without the risk of being identified by their face. The challenge lies in the contradiction of preserving emotional content and successful anonymization. To achieve this goal, avatarization by facial landmark detection is employed. In a user study with 30 participants we achieved an unweighted average recall of 48.6% for facial recognition task, confirming anonymity, while preserving emotional expressivity with an accuracy of 93.3% for happiness, 68.3% for fear, 50.05% for anger and 35.5% for disgust. Thus creating a safe environment for the
user, while preserving emotional content for therapeutic purposes.
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