CASIA OpenIR  > 模式识别实验室
SAS: Painting Detection and Recognition via Smart Art System With Mobile Devices
Wang, Zhenyu1; Lian, Jie1; Song, Chunfeng2; Zhang, Zhaoxiang2; Zheng, Wei1; Yue, Shaolong1; Ji, Senrong1
Source PublicationIEEE ACCESS
ISSN2169-3536
2019
Volume7Pages:135563-135572
Corresponding AuthorWang, Zhenyu(zywang@ncepu.edu.cn)
AbstractArtwork recognition is an important research direction in the field of image processing. However, most of the current proposed methods are not designed for the demand of real-time analysis with mobile devices. Moreover, existing methods usually rely on high quality images and require large amounts of computing consumption. Based on the deep learning technology, in this paper, we propose a Smart Art System (SAS) with mobile devices. Our SAS mainly consists of two parts, i.e., painting detection unit and recognition unit. The detection module adopts a new painting detection algorithm called Single Shot Detection with Painting Landmark Location (SSD-PLL). SSD-PLL can effectively eliminate the influence of complex background factors on recognition. Considering the limited computing capacity of the mobile devices, our recognition module adopts a new ultra-light painting classifier. The classifier adopts MobileNet as the backbone and owns extra operation for Local Features Fusion (LFF). With our SAS, users can use mobile phone to take a photo of any paintings, then SAS would analyze the paintings and report the relevant information in real time. In order to validate the effectiveness of the proposed method, we have established two large scale image databases. The databases include 7,500 Traditional Chinese paintings (TCPs) and 8,800 Oil paintings (OPs), respectively. We evaluate our method and compare with the relevant algorithms, and our method achieves the highest performance and better real-time performance. Extensive experimental results on these databases show the effectiveness of the proposed algorithm.
KeywordMobile devices deep learning painting detection and recognition
DOI10.1109/ACCESS.2019.2941239
WOS KeywordCLASSIFICATION ; NETWORKS
Indexed BySCI
Language英语
Funding ProjectNational Natural Science Foundation of China[61976090] ; National Natural Science Foundation of China[61573139] ; Fundamental Research Funds for the Central Universities[2018ZD05] ; National Natural Science Foundation of China[61976090] ; National Natural Science Foundation of China[61573139] ; Fundamental Research Funds for the Central Universities[2018ZD05]
Funding OrganizationNational Natural Science Foundation of China ; Fundamental Research Funds for the Central Universities
WOS Research AreaComputer Science ; Engineering ; Telecommunications
WOS SubjectComputer Science, Information Systems ; Engineering, Electrical & Electronic ; Telecommunications
WOS IDWOS:000498680900012
PublisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Citation statistics
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/29366
Collection模式识别实验室
Corresponding AuthorWang, Zhenyu
Affiliation1.North China Elect Power Univ, Sch Control & Comp Engn, Beijing 102206, Peoples R China
2.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100080, Peoples R China
Recommended Citation
GB/T 7714
Wang, Zhenyu,Lian, Jie,Song, Chunfeng,et al. SAS: Painting Detection and Recognition via Smart Art System With Mobile Devices[J]. IEEE ACCESS,2019,7:135563-135572.
APA Wang, Zhenyu.,Lian, Jie.,Song, Chunfeng.,Zhang, Zhaoxiang.,Zheng, Wei.,...&Ji, Senrong.(2019).SAS: Painting Detection and Recognition via Smart Art System With Mobile Devices.IEEE ACCESS,7,135563-135572.
MLA Wang, Zhenyu,et al."SAS: Painting Detection and Recognition via Smart Art System With Mobile Devices".IEEE ACCESS 7(2019):135563-135572.
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