基于深度学习的视频检索系统设计与实现

Design and Implementation of Video Retrieval SystemBased on Deep Learning

摘要:

针对摄像头产生的海量视频信息,检索工作需要花费大量的人力、物力以及时间成本问题,分析发现传统检索的功能大多都基于文本关键词,对视频内容的覆盖率低且容易依赖于相关工作人员的主观性。提出如何应用传统的机器视觉技术以及深度学习技术去构建一个高效的视频检索系统。创新点在于从视频帧图像内容的角度去充分发掘其中的信息,其信息挖掘的过程无需人工干预,从而提高了信息利用率。

Abstract:

In view of the huge amount of video information generated by the camera, the retrieval work needs a lot of manpower, material resources and time cost. The analysis shows that most of the traditional retrieval functions are based on text Keywords, and the coverage of video content is low and easy to rely on the subjectivity of the relevant staff. This paper proposes how to use traditional machine vision technology and deep learning technology to build an efficient video retrieval system. The innovation lies in fully exploring the information from the perspective of video frame image content. The process of information mining does not need manual intervention, thus improving the utilization rate of information.