Touch Challenge '15: Recognizing Social Touch Gestures

Merel M. Jung, Laura Cang, M. Poel, Karon E Maclean
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引用次数: 35

Abstract

Advances in the field of touch recognition could open up applications for touch-based interaction in areas such as Human-Robot Interaction (HRI). We extended this challenge to the research community working on multimodal interaction with the goal of sparking interest in the touch modality and to promote exploration of the use of data processing techniques from other more mature modalities for touch recognition. Two data sets were made available containing labeled pressure sensor data of social touch gestures that were performed by touching a touch-sensitive surface with the hand. Each set was collected from similar sensor grids, but under conditions reflecting different application orientations: CoST: Corpus of Social Touch and HAART: The Human-Animal Affective Robot Touch gesture set. In this paper we describe the challenge protocol and summarize the results from the touch challenge hosted in conjunction with the 2015 ACM International Conference on Multimodal Interaction (ICMI). The most important outcomes of the challenges were: (1) transferring techniques from other modalities, such as image processing, speech, and human action recognition provided valuable feature sets; (2) gesture classification confusions were similar despite the various data processing methods used.
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触摸挑战’15:识别社交触摸手势
触摸识别领域的进步将为人机交互(HRI)等领域的基于触摸的交互开辟应用。我们将这一挑战扩展到致力于多模态交互的研究社区,目的是激发人们对触摸模态的兴趣,并促进探索使用来自其他更成熟的触摸识别模态的数据处理技术。有两个数据集包含社交触摸手势的标记压力传感器数据,这些数据是通过用手触摸触摸敏感的表面来执行的。每个集合都是从相似的传感器网格中收集的,但在反映不同应用方向的条件下:CoST: Social Touch语料库和HAART:人类-动物情感机器人触摸手势集。在本文中,我们描述了挑战协议,并总结了与2015年ACM国际多模态交互会议(ICMI)一起主办的触摸挑战的结果。这些挑战最重要的结果是:(1)从其他模式(如图像处理、语音和人类动作识别)转移技术提供了有价值的特征集;(2)尽管使用了不同的数据处理方法,但手势分类混淆相似。
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