Recognizing facial activity is a well-understood (but non-trivial) computer vision problem.
However, reliable solutions require a camera with a good view of the face, which is often …

Affective computing often relies on audiovisual data to identify affective states from non-
verbal signals, such as facial expressions and vocal cues. Since automatic affect recognition …

Smart speaker voice assistants (VAs) such as Amazon Echo and Google Home have been
widely adopted due to their seamless integration with smart home devices and the Internet …

Ethical affective computing (AC) requires maximizing the benefits to users while minimizing
its harm to obtain trust from users. This requires responsible development and deployment …

We applied techniques from psychology---typically used to visualize human bias---to facial
analysis systems, providing novel approaches for diagnosing and communicating …

Facial emotion recognition (FER) from images or videos is an emerging subfield of emotion
recognition that in recent years has achieved increased traction resulting in a wide range of …

We present a novel approach to mitigate bias in facial expression recognition (FER) models.
Our method aims to reduce sensitive attribute information such as gender, age, or race, in …

Facial expression recognition is vital for human behavior analysis, and deep learning has
enabled models that can outperform humans. However, it is unclear how closely they mimic …

Gender bias is one of the types of bias studied in fair machine learning (ML), which seeks
equity in the predictions made by ML models. Bias mitigation is often based on protecting …

Image recognition algorithms have been an integral part of computer security systems since
the early days of the technology. Although a typical username and password can be …