关键词: 深度学习, 视频跟踪, 卷积神经网络, 递归神经网络, 自编码器

Abstract: In recent years, deep learning has developed rapidly. It has overturned the design of algorithms for speech recognition, image classification and text understanding. Because of its strong feature extraction ability, deep learning has achieved outstanding results in the field of image recognition. However, the combination of deep learning and video surveillance is not much. Because the depth model has a multi-layer network structure and the complexity of the algorithm is large, it takes time to train and update the model, and it is difficult to meet the real-time requirements. This paper reviews the development history of deep learning, and introduces the main model of deep learning in the last 10 years. Then, this paper discusses the target tracking algorithm based on deep learning and points out the advantages and disadvantages of each algorithm. Finally, the current problems and development prospects in this field are summarized and prospected.

Key words: deep learning, video tracking, convolutional neural network, recurrent neural network, autoencoder