基于深度学习的视频中人体动作识别进展综述

视频中的人体动作识别是计算机视觉领域内一个充满挑战的课题.不论是在视频信息检索、日常生活安全、公共视频监控，还是人机交互、科学认知等领域都有广泛的应用.本文首先简单介绍了动作识别的研究背景、意义及其难点，接着从模型输入信号的类型和数量、是否结合了传统特征提取方法、模型预训练三个维度详细综述了基于深度学习的动作识别方法，及比较分析了它们在UCF101和HMDB51这两个数据集上的识别效果.最后分别从视频预处理、视频中人体运动信息表征、模型学习训练这三个角度对未来动作识别可能的发展方向进行了论述.

The Progress of Human Action Recognition in Videos Based on Deep Learning: A Review

Human action recognition in videos is a challenging topic in the field of computer vision.It is widely not only used in video information retrieval,daily life security,public video surveillance,but also human-computer interaction,scientific cognition and other fields.First,the research background,research significance and difficulties of action recognition are briefly introduced,and then the deep learning model based action recognition methods are comprehensively reviewed from three different aspects:the types and numbers of input signals,the combination with traditional feature extraction methods,and the pre-trained datasets.Furthermore,the performances of some typical methods on UCF101 and HMDB51 datasets are overviewed and analyzed.Last the possible future research directions are discussed from three perspectives:the video data preprocessing,the video human motion feature representation,and the model training.