基于3D卷积神经网络的视频哈希算法

Video hash algorithm based on 3D convolutional neural network

针对目前相似性视频检索方法中快速性和准确性仍无法满足用户要求等问题,提出了一种基于3D卷积神经网络的视频快速检索方法。该算法将3D卷积神经网络与哈希学习方法结合应用于视频数据,既能快速学习视频时空特征表示,又能极大地缩短视频检索时间。在常用视频数据集上的实验结果表明,利用所提出的方法对视频进行相似性检索性能优于当前主流方法。

In order to solve the problem that the speed and accuracy of the current similarity video retrieval methods still cannot meet the requirements of users,this paper proposed a new similarity video quick retrieval method,which combined the three-dimensional convolutional neural network with the hash learning method and applied to video data.It could not only quickly learn the video spatiotemporal feature representation,but also greatly shorten the video retrieval time.The experimental results on the set show that the similarity retrieval performance of the video using the proposed method is superior to the current mainstream methods.