Fisher vector for scene character recognition: A comprehensive evaluation
Shi, Cunzhao; Wang, Yanna; Jia, Fuxi; He, Kun; Wang, Chunheng; Xiao, Baihua
发表期刊PATTERN RECOGNITION
2017-12-01
卷号72期号:2017页码:1-14
文章类型Article
摘要Fisher vector (FV), which could be seen as a bag of visual words (BOW) that encodes not only word counts but also higher-order statistics, works well with linear classifiers and has shown promising performance for image categorization. For character recognition, although standard BOW has been applied, the results are still not satisfactory. In this paper, we apply Fisher vector derived from Gaussian Mixture Models (GMM) based visual vocabularies on character recognition and integrate spatial information as well. We, give a comprehensive evaluation of Fisher vector with linear classifier on a series of challenging English and digits character recognition datasets, including both the handwritten and scene character recognition ones. Moreover, we also collect two Chinese scene character recognition datasets to evaluate the suitability of Fisher vector to represent Chinese characters. Through extensive experiments we make three contributions: (1) we demonstrate that FV with linear classifier could outperform most of the state-of-the-art methods for character recognition, even the CNN based ones and the superiority is more obvious when training samples are insufficient to train the networks; (2) we show that additional spatial information is very useful for character representation, especially for Chinese ones, which have more complex structures; and (3) the results also imply the potential of FV to represent new unseen categories, which is quite inspiring since it is quite difficult to collect enough training samples for large-category Chinese scene characters. (C) 2017 Elsevier Ltd. All rights reserved.
关键词Character Representation Character Recognition Fisher Vector (Fv) Gaussian Mixture Models (Gmm) Bag Of Visual Words (Bow)
WOS标题词Science & Technology ; Technology
DOI10.1016/j.patcog.2017.06.022
关键词[WOS]TEXT RECOGNITION ; OBJECT RECOGNITION ; GENERATIVE MODELS ; REPRESENTATION ; CLASSIFICATION ; HISTOGRAM ; IMAGES
收录类别SCI
语种英语
项目资助者National Natural Science Foundation of China (NSFC)(61601462 ; 61531019 ; 71621002)
WOS研究方向Computer Science ; Engineering
WOS类目Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic
WOS记录号WOS:000411545400001
引用统计
被引频次:7[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/173211/19548
专题复杂系统管理与控制国家重点实验室_影像分析与机器视觉
作者单位Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, 95 Zhongguancun East Rd, Beijing 100190, Peoples R China
推荐引用方式
GB/T 7714
Shi, Cunzhao,Wang, Yanna,Jia, Fuxi,et al. Fisher vector for scene character recognition: A comprehensive evaluation[J]. PATTERN RECOGNITION,2017,72(2017):1-14.
APA Shi, Cunzhao,Wang, Yanna,Jia, Fuxi,He, Kun,Wang, Chunheng,&Xiao, Baihua.(2017).Fisher vector for scene character recognition: A comprehensive evaluation.PATTERN RECOGNITION,72(2017),1-14.
MLA Shi, Cunzhao,et al."Fisher vector for scene character recognition: A comprehensive evaluation".PATTERN RECOGNITION 72.2017(2017):1-14.
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