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人体点光动作的生物性与非生物性:数据集的创建与验证。

Human biological and nonbiological point-light movements: Creation and validation of the dataset.

机构信息

Social and Cognitive Neuroscience Laboratory and Developmental Disorders Program, Center for Healthy and Biological Sciences, Mackenzie Presbyterian University, Rua Piaui, 181, 10th floor, Consolação, 01241-001, Sao Paulo, SP, Brazil.

Laboratory of Movement Sciences, Center for Healthy and Biological Sciences, Mackenzie Presbyterian University, Sao Paulo, Brazil.

出版信息

Behav Res Methods. 2017 Dec;49(6):2083-2092. doi: 10.3758/s13428-016-0843-9.

DOI:10.3758/s13428-016-0843-9
PMID:28004359
Abstract

Human action perception is so powerful that people can identify movement efficiently in the absence of pictorial information, such as in point-light displays. Interest is growing in this type of stimulus for research in neuroscience. This interest stems from the advantage of separating the component of pure human action kinematics from other pictorial information, such as facial expression and muscle contraction. Although several groups have previously developed datasets of human point-light actions, due to the lack of datasets composed of daily actions with short durations, we developed 20 biological and 40 control (scrambled) point-light movements by using the technique of recording people wearing reflector patches. The videos are about 1 s long. Subsequently, we performed a judgment task in which 100 participants (50 male and 50 female) evaluated each video according to three categories: human action resemblance, performed action, and gender of actor. We present the mean scores of each evaluation for each video, and further propose a selection of the most suitable videos to be used as human point-light action displays and scrambled point-light displays for control. Finally, we discuss our findings on the gender attributions of the point-light displays.

摘要

人类动作感知能力非常强大,即使没有图像信息,例如点光显示,人们也能高效地识别动作。这种类型的刺激物在神经科学研究中越来越受到关注。这种兴趣源于将纯人类动作运动学的组成部分与其他图像信息(例如面部表情和肌肉收缩)分离的优势。尽管以前有几个小组已经开发了人类点光动作的数据集,但由于缺乏由持续时间短的日常动作组成的数据集,我们使用记录穿着反射器贴片的人的技术开发了 20 个生物和 40 个对照(混淆)点光运动。视频时长约为 1 秒。随后,我们进行了一项判断任务,其中 100 名参与者(50 名男性和 50 名女性)根据三个类别评估每个视频:人类动作相似性、执行的动作和演员的性别。我们给出了每个视频的每个评估的平均分数,并进一步提出了选择最合适的视频作为人类点光动作显示和对照点光显示的混淆点光显示。最后,我们讨论了我们对点光显示的性别归因的发现。

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SmartDetector: Automatic and vision-based approach to point-light display generation for human action perception.SmartDetector:一种基于自动视觉的点光显示生成方法,用于人类动作感知。
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Decoding point-light displays and fully visible hand grasping actions within the action observation network.在动作观察网络中解码点光显示和完全可见的手部抓取动作。
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