Writer Identification Using GMM Supervectors and Exemplar-SVMs

详细信息    查看全文

• 作者：Vincent Christlein ; ^{vincent.christlein@fau.de}Author Vitae ; David Bernecker ^{david.bernecker@fau.de}Author Vitae ; Florian Hö ; nig ^{florian.hoenig@fau.de}Author Vitae ; Andreas Maier ^{andreas.maier@fau.de}Author Vitae ; Elli Angelopoulou ^{elli.angelopoulou@fau.de}Author Vitae
• 关键词：Writer identification ; GMM supervectors ; Exemplar-SVM
• 刊名：Pattern Recognition
• 出版年：2017
• 出版时间：March 2017
• 年：2017
• 卷：63
• 期：Complete
• 页码：258-267
• 全文大小：699 K
• 卷排序：63

文摘

We provide a robust method for offline writer identification. We integrate Exemplar-SVMs, which greatly improve the recognition rate. We show that RootSIFT descriptors sampled at the contour are strong features. We investigate different encoding strategies next to GMM supervectors. We evaluate our method on three publicly available datasets (ICDAR13, CVL, KHATT).