从野外多模态数据建模社会情绪和认知过程

Dennis Küster, F. Putze, Patrícia Alves-Oliveira, Maike Paetzel, T. Schultz
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引用次数: 4

摘要

在野外检测、建模和理解来自人类用户的多模态数据仍然面临许多挑战。从我们的测量仪器的数据质量和可靠性方面开始,开发人机或人机交互(HCI, HRI)的智能自适应系统的多学科努力需要广泛的专业知识和更综合的努力,以使这些系统可靠,引人入胜和用户友好。与此同时,机器学习和野外多模态数据建模的应用范围不断扩大。从教室到机器人辅助手术室,我们的研讨会旨在支持关于野外多模态数据建模领域的当前趋势和方法的活跃交流。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Modeling Socio-Emotional and Cognitive Processes from Multimodal Data in the Wild
Detecting, modeling, and making sense of multimodal data from human users in the wild still poses numerous challenges. Starting from aspects of data quality and reliability of our measurement instruments, the multidisciplinary endeavor of developing intelligent adaptive systems in human-computer or human-robot interaction (HCI, HRI) requires a broad range of expertise and more integrative efforts to make such systems reliable, engaging, and user-friendly. At the same time, the spectrum of applications for machine learning and modeling of multimodal data in the wild keeps expanding. From the classroom to the robot-assisted operation theatre, our workshop aims to support a vibrant exchange about current trends and methods in the field of modeling multimodal data in the wild.
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