Abstract
This work introduces a real-time system able to lead humanoid robot behavior depending on the gender of the interacting person. It exploits Aldebaran NAO humanoid robot view capabilities by applying a gender prediction algorithm based on the face analysis. The system can also manage multiple persons at the same time, recognizing if the group is composed by men, women or is a mixed one and, in the latter case, to know the exact number of males and females, customizing its response in each case. The system can allow for applications of human-robot interaction requiring an high level of realism, like rehabilitation or artificial intelligence.
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https://community.aldebaran-robotics.com/doc/1-14/index.html
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Carcagnì, P., Cazzato, D., Del Coco, M., Leo, M., Pioggia, G., Distante, C. (2014). Real-Time Gender Based Behavior System for Human-Robot Interaction. In: Beetz, M., Johnston, B., Williams, MA. (eds) Social Robotics. ICSR 2014. Lecture Notes in Computer Science(), vol 8755. Springer, Cham. https://doi.org/10.1007/978-3-319-11973-1_8
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DOI: https://doi.org/10.1007/978-3-319-11973-1_8
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