论文标题
3D卷积网络以进行行动识别：适用于运动手势识别
3D Convolutional Networks for Action Recognition: Application to Sport Gesture Recognition
论文作者
论文摘要
3D卷积网络是执行诸如视频分割诸如目标分类法的连贯时空块以及对其分类的诸如视频分割之类的好方法。在本章中，我们对连续视频的分类感兴趣，例如可重复的动作，例如乒乓球的笔触。这些视频在不太生态环境中拍摄，从分割和分类的角度来看是一个挑战。 3D Convnets是通过基于窗口的方法解决这些问题的有效工具。
3D convolutional networks is a good means to perform tasks such as video segmentation into coherent spatio-temporal chunks and classification of them with regard to a target taxonomy. In the chapter we are interested in the classification of continuous video takes with repeatable actions, such as strokes of table tennis. Filmed in a free marker less ecological environment, these videos represent a challenge from both segmentation and classification point of view. The 3D convnets are an efficient tool for solving these problems with window-based approaches.
