FG '00 Proceedings of the Fourth IEEE International Conference on Automatic Face and Gesture Recognition 2000
Feature Extraction and Selection for Inferring User Engagement in an HCI Environment
Proceedings of the 13th International Conference on Human-Computer Interaction. Part I: New Trends
Detecting user engagement with a robot companion using task and social interaction-based features
Proceedings of the 2009 international conference on Multimodal interfaces
Computer Vision and Image Understanding - Special issue on eye detection and tracking
Automatic analysis of affective postures and body motion to detect engagement with a game companion
Proceedings of the 6th international conference on Human-robot interaction
Adaptive view-based appearance models
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
Multimodal detection of salient behaviors of approach-avoidance in dyadic interactions
Proceedings of the 14th ACM international conference on Multimodal interaction
Proceedings of the 2013 on Emotion recognition in the wild challenge and workshop
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Analysis of non-verbal behaviors in HCI allows understanding how individuals apprehend and adapt to different situations of interaction. This seems particularly relevant when considering tasks such as speaking in a foreign language, which is known to elicit anxiety. This is even truer for young users for whom negative pedagogical feedbacks might have a strong negative impact on their motivation to learn. In this paper, we consider the approach-avoidance behaviors of teenagers speaking with virtual agents when using an e-learning platform for learning English. We designed an algorithm for processing the video of these teenagers outside laboratory conditions (e.g. a classical collective classroom in a secondary school) using a webcam. This algorithm processes the video of the user and computes the inter-ocular distance. The anxiety of the users is also collected with questionnaires. Results show that the inter-ocular distance enables to discriminate between approach and avoidance behaviors of teenagers reacting to positive or negative stimulus. This simple metric collected via video processing enables to detect an approach behavior related to a positive stimulus and an avoidance behavior related to a negative stimulus. Furthermore, we observed that these automatically detected approach-avoidance behaviors are correlated with anxiety.