西北师范大学学报（自然科学版）Issue(3)：49-53,5.
基于隐空间的低秩稀疏子空间聚类
Low-rank sparse subspace clustering in latent space
摘要
Abstract
T his paper proposed a novel algorithm named low‐rank sparse subspace clustering in latent space (LatLRSSC ) , it can reduce the dimension and cluster the data lying in a union of subspaces simultaneously . The main advatages of our method is that it is computationally efficient . The effectiveness of the algorithm is demonstrated through experiments on motion segmentation and face clustering .关键词
子空间聚类/稀疏表示/低秩表示/运动分割/人脸聚类Key words
subspace clustering/sparse representation/low-rank representation/motion segmentation/face clustering分类
信息技术与安全科学引用本文复制引用
刘建华..基于隐空间的低秩稀疏子空间聚类[J].西北师范大学学报（自然科学版）,2015,(3):49-53,5.基金项目
浙江省自然科学基金资助项目 （）
