关键词: 视频目标检测, 卷积神经网络, 关联特征

Abstract: The problem of mutual restriction between speed and precision caused by using image detection algorithm in the field of video object detection，a video detection method based on correlation features and convolutional neu- ral network is proposed in order to make full use of the target’s motion between frames． Our methods are demon- strated as follows: firstly，an image detection algorithm is used to extract features from the current video frame; sec- ondly，the correlation features between the frames is employed to predict the feature maps of the current frame and finally，the target motion information from the associated features is used to predict the final result． The method proposed in this paper finally experimented on the ImageNet dataset，which is proved better than the current method since the precision is enhanced and a faster speed is maintained．

Key words: video object detection, convolutional neural network, correlation feature