A Sparse Projection and Low-Rank Recovery Framework for Handwriting Representation and Salient Stroke Feature Extraction
Zhang, Zhao1; Liu, Cheng-Lin2; Zhao, Ming-Bo3
2015-04-01
发表期刊ACM TRANSACTIONS ON INTELLIGENT SYSTEMS AND TECHNOLOGY
卷号6期号:1
文章类型Article
摘要In this article, we consider the problem of simultaneous low-rank recovery and sparse projection. More specifically, a new Robust Principal Component Analysis (RPCA)-based framework called Sparse Projection and Low-Rank Recovery (SPLRR) is proposed for handwriting representation and salient stroke feature extraction. In addition to achieving a low-rank component encoding principal features and identify errors or missing values from a given data matrix as RPCA, SPLRR also learns a similarity-preserving sparse projection for extracting salient stroke features and embedding new inputs for classification. These properties make SPLRR applicable for handwriting recognition and stroke correction and enable online computation. A cosine-similarity-style regularization term is incorporated into the SPLRR formulation for encoding the similarities of local handwriting features. The sparse projection and low-rank recovery are calculated from a convex minimization problem that can be efficiently solved in polynomial time. Besides, the supervised extension of SPLRR is also elaborated. The effectiveness of our SPLRR is examined by extensive handwritten digital repairing, stroke correction, and recognition based on benchmark problems. Compared with other related techniques, SPLRR delivers strong generalization capability and state-of-the-art performance for handwriting representation and recognition.
关键词Algorithms Design Experimentation Performance Sparse Projection Low-rank Recovery Similarity Preservation Salient Stroke Feature Extraction HAndwriting Representation And Recognition
WOS标题词Science & Technology ; Technology
关键词[WOS]FACE RECOGNITION ; PRESERVING PROJECTIONS ; CLASSIFICATION ; ALGORITHM
收录类别SCI
语种英语
WOS研究方向Computer Science
WOS类目Computer Science, Artificial Intelligence ; Computer Science, Information Systems
WOS记录号WOS:000353638800009
引用统计
被引频次:2[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://ir.ia.ac.cn/handle/173211/8116
专题模式识别国家重点实验室_模式分析与学习
作者单位1.Soochow Univ, Sch Comp Sci & Technol, Suzhou 215006, Peoples R China
2.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
3.City Univ Hong Kong, Dept Elect Engn, Kowloon, Hong Kong, Peoples R China
推荐引用方式
GB/T 7714
Zhang, Zhao,Liu, Cheng-Lin,Zhao, Ming-Bo. A Sparse Projection and Low-Rank Recovery Framework for Handwriting Representation and Salient Stroke Feature Extraction[J]. ACM TRANSACTIONS ON INTELLIGENT SYSTEMS AND TECHNOLOGY,2015,6(1).
APA Zhang, Zhao,Liu, Cheng-Lin,&Zhao, Ming-Bo.(2015).A Sparse Projection and Low-Rank Recovery Framework for Handwriting Representation and Salient Stroke Feature Extraction.ACM TRANSACTIONS ON INTELLIGENT SYSTEMS AND TECHNOLOGY,6(1).
MLA Zhang, Zhao,et al."A Sparse Projection and Low-Rank Recovery Framework for Handwriting Representation and Salient Stroke Feature Extraction".ACM TRANSACTIONS ON INTELLIGENT SYSTEMS AND TECHNOLOGY 6.1(2015).
条目包含的文件
条目无相关文件。
个性服务
推荐该条目
保存到收藏夹
查看访问统计
导出为Endnote文件
谷歌学术
谷歌学术中相似的文章
[Zhang, Zhao]的文章
[Liu, Cheng-Lin]的文章
[Zhao, Ming-Bo]的文章
百度学术
百度学术中相似的文章
[Zhang, Zhao]的文章
[Liu, Cheng-Lin]的文章
[Zhao, Ming-Bo]的文章
必应学术
必应学术中相似的文章
[Zhang, Zhao]的文章
[Liu, Cheng-Lin]的文章
[Zhao, Ming-Bo]的文章
相关权益政策
暂无数据
收藏/分享
所有评论 (0)
暂无评论
 

除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。