English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Tools annual

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

Human-robot interaction (HRI) benefits greatly from advances in the machinelearning field as it allows researchers to employ high-performance models forperceptual tasks like detection and recognition. Especially deep learningmodels, either pre-trained for feature extraction or used for classification,are now established methods to characterize human behaviors in HRI scenariosand to have social robots that understand better those behaviors. As HRIexperiments are usually small-scale and constrained to particular labenvironments, the questions are how well can deep learning models generalize tospecific interaction scenarios, and further, how good is their robustnesstowards environmental changes? These questions are important to address if theHRI field wishes to put social robotic companions into real environments actingconsistently, i.e. changing lighting conditions or moving people should stillproduce the same recognition results. In this paper, we study the impact ofdifferent image conditions on the recognition of arousal and valence from humanfacial expressions using the FaceChannel framework \cite{Barro20}. Our resultsshow how the interpretation of human affective states can differ greatly ineither the positive or negative direction even when changing only slightly theimage properties. We conclude the paper with important points to consider whenemploying deep learning models to ensure sound interpretation of HRIexperiments.

I am Only Happy When There is Light: The Impact of Environmental Changes on Affective Facial Expressions Recognition