This paper presents a novel architecture to detect social groups in real-time from a continuous image stream of an ego-vision camera. F-formation defines social orientations in space where two or more person tends to communicate in a social place. Thus, essentially, we detect F-formations in social gatherings such as meetings, discussions, etc. and predict the robot's approach angle if it wants to join the social group. Additionally, we also detect outliers, i.e., the persons who are not part of the group under consideration. Our proposed pipeline consists of -- a) a skeletal key points estimator (a total of 17) for the detected human in the scene, b) a learning model (using a feature vector based on the skeletal points) using CRF to detect groups of people and outlier person in a scene, and c) a separate learning model using a multi-class Support Vector Machine (SVM) to predict the exact F-formation of the group of people in the current scene and the angle of approach for the viewing robot. The system is evaluated using two data-sets. The results show that the group and outlier detection in a scene using our method establishes an accuracy of 91%. We have made rigorous comparisons of our systems with a state-of-the-art F-formation detection system and found that it outperforms the state-of-the-art by 29% for formation detection and 55% for combined detection of the formation and approach angle.
Employing Socially Interactive Agents for Robotic Neurorehabilitation Training
German Research Center for Artificial Intelligence（德国人工智能研究中心）；National Research Council of Italy（意大利国家研究委员会）；Augsburg University（奥格斯堡大学）；Scientific Institute IRCCS E. Medea（E.梅迪亚IRCCS科学研究所）
MuMMER: Socially Intelligent Human-Robot Interaction in Public Spaces
University of Glasgow（格拉斯哥大学）；Heriot-Watt University（赫瑞-瓦特大学）；Idiap Research Institute（Idiap研究所）；LAAS-CNRS（法国国家科学研究中心分析与系统架构实验室）；SoftBank Robotics Europe（软银机器人欧洲公司）；VTT Technical Research Centre of Finland（芬兰技术研究中心）
ViLAM: Distilling Vision-Language Reasoning into Attention Maps for Social Robot Navigation
Dept. of Electrical and Computer Engineering, University of Maryland, College Park, MD, USA（电气与计算机工程系，马里兰大学，College Park, MD, USA）；Dept. of Computer Science, University of Maryland, College Park, MD, USA（计算机科学系，马里兰大学，College Park, MD, USA）；James Clark School of Engineering, University of Maryland, College Park, MD, USA（James Clark工程学院，马里兰大学，College Park, MD, USA）
Socially Interactive Agents for Robotic Neurorehabilitation Training: Conceptualization and Proof-of-concept Study
German Research Center for Artificial Intelligence（德国人工智能研究中心）；Human-Centered Artificial Intelligence, Augsburg University（奥格斯堡大学以人为中心的人工智能研究所）；National Research Council of Italy（意大利国家研究委员会）；University of Bologna（博洛尼亚大学）；Scientific Institute IRCCS E. Medea（IRCCS E. Medea科学研究所）
Detecting socially interacting groups using f-formation: A survey of taxonomy, methods, datasets, applications, challenges, and future research directions
TCS Research（塔塔咨询服务研究中心）；Myanmar Institute of Information Technology（缅甸信息技术学院）
