智能系统学报2023，Vol.18Issue(6)：1223-1232,10.DOI:10.11992/tis.202303049
多图融合约束半非负矩阵分解的动作分割方法
Action segmentation based on multigraph fusion constraint semi-nonnegative matrix factorization
摘要
Abstract
Most clustering-based action segmentation methods mainly exploit the structure similarity information between adjacent frames(points)in the sequence to improve the accuracy of action segmentation.These methods im-prove the consistency of segmentation inside each action but introduce potential issues for accurately segmenting action boundaries.Hence,this paper presents a novel action segmentation method based on multigraph fusion constraint semi-nonnegative matrix factorization(MGSeNMF).In this method,the structural and measurement similarity information is fused to build a multigraph fusion constraint term,which is fused to semi-NMF to obtain a low-dimensional representa-tion.A k-nearest neighbor graph is also generated for the action sequences,realizing accurate segmentation using the graph cut method.Experimental results on two kinds of real-action datasets show that MGSeNMF can accurately divide the boundary of actions while maintaining consistent segmentation inside each action.Thus,the proposed method im-proves the accuracy of segmentation and efficiency of running time significantly.关键词
动作分割/聚类/半非负矩阵分解/多图融合约束/结构相似性/度量相似性/低维表示/k近邻图Key words
action segmentation/clustering/semi-NMF/multigraph fusion constraint/structural similarity/measure-ment similarity/low-dimensional representation/k-nearest neighbor graph分类
信息技术与安全科学引用本文复制引用
李国朋,王连清,韩鹍,王宇弘,宋聃,余立..多图融合约束半非负矩阵分解的动作分割方法[J].智能系统学报,2023,18(6):1223-1232,10.基金项目
国家自然科学基金项目(62101558) （62101558）
陕西省自然科学基础研究计划(2022JM-395) （2022JM-395）
国防科技大学科研计划项目(ZK21-38). （ZK21-38）
