辽宁工程技术大学学报（自然科学版）2025，Vol.44Issue(1)：120-128,9.
基于视频帧间局部相关信息的光流估计网络
Optical flow estimation via fusing sequence image intensity correlation information
摘要
Abstract
To address the challenges associated with inaccurate target edge segmentation,motion speed,and motion direction,this paper introduces an optical flow estimation network that leverages local correlation information between video frames.Initially,the network employs a feature encoder to extract encoding features from the image and capture contextual information through a context network.Subsequently,the feature size is reduced through downsampling to enhance computational efficiency.Given the minute displacement of the optical flow image across consecutive frames,a partition-based visual similarity computation method is proposed to construct a more refined 4D correlation volume.Residual filters and similar convolution blocks are utilized for processing the correlation volume and optical flow information,respectively,ensuring the preservation of local small displacement details.The research results show that the optical flow estimation network based on the local correlation information between video frames has achieved optimizations of 8.0%and 5.7%respectively in the optical flow estimation evaluation metric(endpoint error,EPE).This significantly improves the accuracy of optical flow estimation and effectively alleviates the problem of inaccurate optical flow information extraction in complex scenarios.The research conclusions provide references for fields such as autonomous driving and intelligent security.关键词
计算机视觉/光流估计/深度学习/区域匹配/迭代更新Key words
computer vision/optical flow estimation/deep learning/regional matching/iterative update分类
信息技术与安全科学引用本文复制引用
徐煦,马鹏飞,司建军,高国军..基于视频帧间局部相关信息的光流估计网络[J].辽宁工程技术大学学报（自然科学版）,2025,44(1):120-128,9.基金项目
国家自然科学基金项目(61601213) （61601213）
