Hand Gesture and Movement Dataset

该数据集是一个包含预定义手势和动作的多样化集合，其中涵盖了角度变化、不同摄像机位置和光照条件。该数据集已经过裁剪和归一化预处理，并使用PyTorch框架用于训练识别网络。在手势识别任务中，所训练的网络达到了94.3%的准确率；而在动态动作识别任务中，准确率更是高达97.6%。这是一个包含多种手势和动作的综合性数据集。

This dataset is a diverse collection of predefined gestures and motions, covering variations in viewing angles, camera positions, and lighting conditions. It has been preprocessed with cropping and normalization operations, and is utilized with the PyTorch framework for training recognition networks. For the gesture recognition task, the trained network achieved an accuracy of 94.3%; while for dynamic motion recognition tasks, the accuracy reached as high as 97.6%. This is a comprehensive dataset encompassing a wide range of gestures and motions.