Acquisition of System for Multi-Site Networked Motion Capture and Visually Immersive Laboratory for Social and Behavioral Research

伦斯勒理工学院将获得美国国家科学基金会的主要研究仪器奖，该学院将获得一个16摄像头的Vicon MX运动捕捉系统，该系统将实时跟踪单个人或物体上多达40个运动点或两个相互作用的人/物体上的20个运动点。由此产生的数据为捕获、分析、建模和再现人类和机器人等复杂物体的非常逼真的运动提供了基础。该系统还将包括动画工作站和软件，将运动点转换为动画对象，该动画对象显示被监视的目标人或对象的运动特征，同时修改人/对象的外部外观。该设备将安装在伦斯勒社会和行为研究实验室，作为500平方英尺的一部分。虚拟现实工作室。由此产生的设施将是极少数能够记录涉及人体和移动物体动力学的数据的学术装置之一。该仪器将用于许多研究领域。这些研究项目的一个共同主题是需要获取有关人类社会和行为动态的丰富数据，目的是回答有关人类如何使用身体运动来理解他们的世界以及交流情感和认知状态的基本问题。这种理解对于开发更好的人-对象和人-人交互模型，以及开发支持下一代人机交互系统的界面策略至关重要。除了提供解决基本理论问题的数据外，该设备还将促进实际HCI应用的发展，例如通过使用全身运动或通过感知和适应情绪状态来更好地支持社会和物理交互的接口。它还将支持开发诊断工具，促进对包括各种社会功能障碍在内的疾病/综合征的理解。该设备将促进伦斯勒理工学院社会科学家和工程师之间的合作。这些合作对于更深入地理解基本的人类社会和行为动态是越来越必要的，这些动态可以被纳入与技术接触的新模式的发展，其目标是鼓励更多以人为本的界面、代理和机器人设计。将利用这些设备的项目包括研究人类在物理空间中的感知和行动、物理和社会推理、非语言交流和信任的动力要素、物理线索对协作有效性的影响、将游戏的激励力量与有益于健康的体育锻炼相结合、模拟舞蹈表演作为数学教育的一种形式、模拟与机器人的社会互动、以及多机器人运动研究中ground truth的发展。该仪器还将作为重要的教育资源，使伦斯勒能够培训下一代社会科学家和工程师收集和分析动态社会和行为数据，并为有兴趣掌握这些技术的学生提供强大的招聘工具，并解决用这种观测设备收集的丰富数据最好回答的问题。

With the National Science Foundation's Major Research Instrumentation Award, Rensselaer Polytechnic Institute will acquire a 16-camera Vicon MX motion capture system that will track up to 40 motion points on a single person or object or 20 points on two interacting people/objects in real time. The resulting data provide the basis for capturing, analyzing, modeling, and reproducing very realistic motion of complex objects like humans and robots. The system will also include an animation workstation and software that will convert the motion points into animated objects that exhibit motion characteristic of the monitored target person or object, while modifying the external appearance of the person/object. The equipment will be installed in the Rensselaer Social and Behavioral Research Laboratory as part of 500 sq. ft. virtual reality studio. The resulting facility will be one of the very few academic installations capable of recording data involving human and moving object kinesics in this detail.The instrumentation will be used in a number of lines of research. A common theme among these research projects is the need for capturing rich data about human social and behavioral dynamics, with the intent of answering basic questions about how human beings use physical motion to understand their world and to communicate affective and cognitive states. This understanding is crucial to the development of better models of human-object and human-human interaction, and to the development of interface strategies to support next-generation systems for human-computer interaction. In addition to providing data addressing basic theoretical questions, the equipment will also foster the development of practical HCI applications, such as interfaces that better support social and physical interaction by using full body motion or by sensing and adapting to emotional states. It will also support development of diagnostic tools that foster the understanding of illnesses/syndromes that include various social dysfunctions. This equipment will facilitate partnerships between social scientists and engineers at Rensselaer Polytechnic Institute. These collaborations are increasingly necessary for a deeper understanding of fundamental human social and behavioral dynamics that can be incorporated into the development of new modes of engagement with technology, with the goal of encouraging more human-centered design of interfaces, agents, and robots.Projects that will make use of the equipment include a study of human perception and action in physical spaces, physical and social reasoning, kinesic elements of nonverbal communication and trust, effects of physical cues on collaboration effectiveness, combining the motivational power of games with physical exercise for health benefits, simulated dance performance as a form of math education, simulation of social interaction with robotics, and the development of ground truth for multiple robot motion studies. The instrumentation will also serve as an important educational resource, enabling Rensselaer to train the next generation of social scientists and engineers in the collection and analysis of dynamic social and behavioral data, and serving as a powerful recruitment tool for students interested in mastering these techniques and addressing questions that are best answered with the kinds of rich data collected with this kind of observational equipment.