Data Set Information:

Vicon运动捕捉摄像头系统用于记录12名使用者在左手手套上贴上标记，进行5种手部姿势。

手套背面的刚性标记图案用于建立手的局部坐标系，另外11个标记附着在手套的拇指和手指上。3个标记附着在拇指上，一个在拇指上方，另两个在指关节上。每个手指上都有2个标记，一个位于指甲上方，另一个位于近中指骨之间的关节上。

不属于刚性模式的11个标记未标记；他们的立场没有被明确跟踪。因此，两个给定记录的标记之间不存在先验对应关系。此外，由于捕获体积的分辨率和手和手指的方向和配置导致的自遮挡，许多记录缺少标记。由于Vicon软件的标记重建/记录过程中的伪影以及捕获体积中的其他对象，也可能存在无关标记。因此，记录中可见标记的数量差异很大。

这里提供的数据已经进行了部分预处理。首先，将所有标记转换为包含它们的记录的局部坐标系。其次，对每一个范数大于200毫米的转化标记进行修剪。最后，删除任何包含少于3个标记的记录。处理后的数据每个记录最多有12个标记，至少有3个。有关详细信息，请参阅“属性信息”。

由于捕获数据的方式，对于给定的记录和用户，可能存在来自同一用户的几乎重复的记录。因此，我们建议在漏掉一个用户的基础上评估分类算法，其中每个用户迭代地从训练中漏掉，并用作测试集。然后测试算法对新用户的通用性。提供“用户”属性以适应此策略。

该数据集可用于各种任务，其中最明显的是通过分类进行姿势识别。还可以尝试用户识别。或者，可以执行聚类（约束或非约束）以发现标记分布，作为预测标记身份或获得姿势的统计描述/可视化的尝试。

在以前的工作中，为了平衡类，我们在不替换的情况下对每个用户的每个类随机抽样了固定数量（例如75个）的记录。

Attribute Information:

Data is provided as a CSV file. A header provides the name of each attribute. An initial dummy record composed entirely of 0s should be ignored. A question mark '?' is used to indicate a missing value. A record corresponds to a single instant or frame as recorded by the camera system.

'Class' - Integer. The class ID of the given record. Ranges from 1 to 5 with 1=Fist(with thumb out), 2=Stop(hand flat), 3=Point1(point with pointer finger), 4=Point2(point with pointer and middle fingers), 5=Grab(fingers curled as if to grab).
'User' - Integer. The ID of the user that contributed the record. No meaning other than as an identifier.
'Xi' - Real. The x-coordinate of the i-th unlabeled marker position. 'i' ranges from 0 to 11.
'Yi' - Real. The y-coordinate of the i-th unlabeled marker position. 'i' ranges from 0 to 11.
'Zi' - Real. The z-coordinate of the i-th unlabeled marker position. 'i' ranges from 0 to 11.

Each record is a set. The i-th marker of a given record does not necessarily correspond to the i-th marker of a different record. One may randomly permute the visible (not missing) markers of a given record without changing the set that the record represents. For the sake of convenience, all visible markers of a given record are given a lower index than any missing marker. A class is not guaranteed to have even a single record with all markers visible.

Relevant Papers:

[1] A. Gardner, J. Kanno, C. A. Duncan, and R. Selmic. 'Measuring distance between unordered sets of different sizes,' in 2014 IEEE Conference on Computer Vision and Pattern Recognition(CVPR), June 2014, pp. 137-143.
[2] A. Gardner, C. A. Duncan, J. Kanno, and R. Selmic. '3D hand posture recognition from small unlabeled point sets,' in 2014 IEEE International Conference on Systems, Man and Cybernetics (SMC), Oct 2014, pp. 164-169.

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[1] A. Gardner, R. R. Selmic, J. Kanno
   Louisiana Tech University
   abg010 '@' latech.edu, rselmic '@' latech.edu, jkanno '@' latech.edu
[2] C. A. Duncan
   Quinnipiac University
   christian.duncan '@' quinnipiac.edu