{"type":"ScholarlyArticle","title":"Learning Social Affordance for Human-Robot Interaction","authors":[{"name":"Tianmin Shu","slug":"tianmin-shu","given":"Tianmin","family":"Shu","affiliation":""},{"name":"Michael S. Ryoo","slug":"michael-s-ryoo","given":"Michael. S.","family":"Ryoo","affiliation":""},{"name":"Song-Chun Zhu","slug":"song-chun-zhu","given":"Song-Chun","family":"Zhu","affiliation":""}],"abstract":"In this paper, we present an approach for robot learning of social affordance from human activity videos. We consider the problem in the context of human-robot interaction: our approach learns structural representations of human-human (and human-object-human) interactions, describing how body-parts of each agent move with respect to each other and what spatial relations they should maintain to complete each sub-event (i.e., sub-goal). This enables the robot to infer its own movement in reaction to the human body motion, allowing it to naturally replicate such interactions.","doi":null,"url":"https://ijcai.org/proceedings/2016/488","pdf":"https://ijcai.org/proceedings/2016/0488.pdf","markdown":"https://ijcai.org/proceedings/2016/488.md","bibtex":"https://ijcai.org/proceedings/2016/bibtex/488","volume":{"slug":"2016","title":"Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2016","url":"https://ijcai.org/proceedings/2016/","year":2016,"location":"New York, NY, USA","dates":"9–15 July 2016","editors":"Subbarao Kambhampati","isbn":"978-1-57735-770-4; 978-1-57735-771-1","publisher":"AAAI Press / International Joint Conferences on Artificial Intelligence","doi_prefix":""},"section":null,"track":"","number":488,"pages":{"first":3454,"last":3460},"keywords":[],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}