沈阳航空航天大学学报2026，Vol.43Issue(4)：88-96,9.DOI:10.3969/j.issn.2095-1248.2026.04.010
时序特征引导的视频目标分割方法
Temporal feature-guided method for video object segmentation
摘要
Abstract
To address the excessive reliance of existing object segmentation methods on optical flow maps and fully leverage the temporal and spatial correlations inherent in video objects,a two-stage method was proposed that first extracts regions of interest(ROI)using the temporal feature information of objects and backgrounds,and then segments objects using spatial saliency features.Firstly,an optical flow anomaly region detector was designed,which used the optical flow field generated by pixel position changes between sequential images as temporal features to learn the differences in temporal features between objects and backgrounds,thereby detecting object positions and guiding the segmentation scope to the ROI where objects were located.Then,the proposed DC-U2 Net was used as a salient object detector to segment salient objects in the ROI,obtain masks,and complete object segmentation.DC-U2 Net further improved the accuracy of object masks by introducing a dual-channel RSU module and residual connection paths.The proposed method was tested on two public datasets and achieved competitive results.On the DAVIS2016 dataset,the J-score,F-score,and G-score reached 83.7,86.7,and 85.2 respectively.Aiming at the characteristics of temporal features and saliency features of video objects,the proposed two-stage video object segmentation method guided by temporal features-guided improves object segmentation accuracy without compromising real-time performance.关键词
时序特征/视频目标分割/深度学习/掩码/两阶段方法Key words
temporal feature/video object segmentation/deep learning/masks/two-stage method分类
信息技术与安全科学引用本文复制引用
朱琳琳,李家勋,刘珈溪,梁宵..时序特征引导的视频目标分割方法[J].沈阳航空航天大学学报,2026,43(4):88-96,9.基金项目
国家自然科学基金(项目编号:61973222) （项目编号:61973222）
辽宁省高校基本科研业务费专项资金资助项目(项目编号:LJ232410143058). （项目编号:LJ232410143058）
