Abstract
We address the problem of facial expression analysis. The proposed approach predicts both basic emotion and valence/arousal values as a continuous measure for the emotional state. Experimental results including cross-database evaluation on the AffectNet, Aff-Wild, and AFEW dataset shows that our approach predicts emotion categories and valence/arousal values with high accuracies and that the simultaneous learning of discrete categories and continuous values improves the prediction of both. In addition, we use our approach to measure the emotional states of users in an Human-Robot-Collaboration scenario (HRC), show how these emotional states are affected by multiple difficulties that arise for the test subjects, and examine how different feedback mechanisms counteract negative emotions users experience while interacting with a robot system.
Highlights
Human-Robot Cooperation (HCR) is a vital approach to increase the efficiency of industrial workflows
Using the AffectNet dataset which contains both labels for discrete emotion classes and V/A values, we examine whether the simultaneous training of emotion classes and V/A leads to an improved classification
Cross-database evaluation To examine how well our approach generalizes to unseen data and because the number of approaches evaluated on the AffectNet dataset is still somewhat limited, we evaluated our approach on the Aff-Wild and AFEW-VA dataset
Summary
Human-Robot Cooperation (HCR) is a vital approach to increase the efficiency of industrial workflows. The main requirements for a productive HCR environment are security and acceptance of robots (Bröhl et al 2019). To ensure the safety of workers and increase confidence in HCR systems, approaches to avoid collisions between humans and robots are essential. The path with minimal probability is selected, while at the same time the robot speed is reduced in accordance with the expected risk of collision. Another approach by Anvaripour et al (2019) uses force myography data and neural networks to predict human movements and increase HCR
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