This paper presents the outcomes of a contest organized to evaluate methods for the online recognition of heterogeneous gestures from sequences of 3D hand poses. The task is the detection of gestures belonging to a dictionary of 16 classes characterized by different pose and motion features. The dataset features continuous sequences of hand tracking data where the gestures are interleaved with non-significant motions. The data have been captured using the Hololens 2 finger tracking system in a realistic use-case of mixed reality interaction. The evaluation is based not only on the detection performances but also on the latency and the false positives, making it possible to understand the feasibility of practical interaction tools based on the algorithms proposed. The outcomes of the contest's evaluation demonstrate the necessity of further research to reduce recognition errors, while the computational cost of the algorithms proposed is sufficiently low.

翻译：本文件介绍了为评价从3D手姿势序列中在线识别不同手势的方法而组织的竞赛的结果;任务是检测属于16个字典的手势,16个字典有不同的姿势和运动特征;数据集具有连续的手动跟踪数据序列,手动与非重大动作相互交织;数据是在现实使用、相互交织的现实互动情况下使用Holorens 2手指跟踪系统采集的;评价不仅基于探测性能,而且基于延缓性和假阳性,从而能够了解根据提议的算法使用实际互动工具的可行性;对辩论的评价结果表明,有必要进一步研究以减少识别错误,而提议的算法的计算成本则非常低。