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Surgical gesture recognition is important for surgical data science and computer-aided intervention.
Balancing methods for single-label data cannot be applied to multi-label problems as they would also resample the samples with high occurrences.
American Sign Language recognition is a difficult gesture recognition problem, characterized by fast, highly articulate gestures.
Despite the recent advances in both fields, annotated facial expression dataset in the context of sign language are still scarce resources.
Automatic surgical gesture recognition is fundamental for improving intelligence in robot-assisted surgery, such as conducting complicated tasks of surgery surveillance and skill evaluation.
Recognizing Families In the Wild (RFIW): an annual large-scale, multi-track automatic kinship recognition evaluation that supports various visual kin-based problems on scales much higher than ever before.
This paper is a brief introduction to our submission to the seven basic expression classification track of Affective Behavior Analysis in-the-wild Competition held in conjunction with the IEEE International Conference on Automatic Face and Gesture Recognition (FG) 2020.
Isolated facial movements, so-called Action Units, can describe combined emotions or physical states such as pain.
More information regarding the Competition and details for how to access the utilized database, are provided in the Competition site: http://ibug. doc. ic. ac. uk/resources/fg-2020-competition-affective-behavior-analysis.