CASIA OpenIR
Plug-and-Play Based Optimization Algorithm for New Crime Density Estimation
Feng, Xiang-Chu1; Zhao, Chen-Ping1,2; Peng, Si-Long3,4; Hu, Xi-Yuan3,4,5; Ouyang, Zhao-Wei1
Source PublicationJOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY
ISSN1000-9000
2019-04-01
Volume34Issue:2Pages:476-493
Corresponding AuthorZhao, Chen-Ping(zcp0378@163.com)
AbstractDifferent from a general density estimation, the crime density estimation usually has one important factor: the geographical constraint. In this paper, a new crime density estimation model is formulated, in which the regions where crime is impossible to happen, such as mountains and lakes, are excluded. To further optimize the estimation method, a learning-based algorithm, named Plug-and-Play, is implanted into the augmented Lagrangian scheme, which involves an off-the-shelf filtering operator. Different selections of the filtering operator make the algorithm correspond to several classical estimation models. Therefore, the proposed Plug-and-Play optimization based estimation algorithm can be regarded as the extended version and general form of several classical methods. In the experiment part, synthetic examples with different invalid regions and samples of various distributions are first tested. Then under complex geographic constraints, we apply the proposed method with a real crime dataset to recover the density estimation. The state-of-the-art results show the feasibility of the proposed model.
Keywordcrime density estimation augmented Lagrangian strategy Plug-and-Play filtering operator
DOI10.1007/s11390-019-1920-1
WOS KeywordIMAGE DECOMPOSITION
Indexed BySCI
Language英语
Funding ProjectNational Natural Science Foundation of China[61772389] ; National Natural Science Foundation of China[61871260] ; Open Project of National Engineering Laboratory for Forensic Science of China[2017NELKFKT02] ; Key Scientific Research Projects in Henan Colleges and Universities of China[19A110015]
Funding OrganizationNational Natural Science Foundation of China ; Open Project of National Engineering Laboratory for Forensic Science of China ; Key Scientific Research Projects in Henan Colleges and Universities of China
WOS Research AreaComputer Science
WOS SubjectComputer Science, Hardware & Architecture ; Computer Science, Software Engineering
WOS IDWOS:000462960800014
PublisherSCIENCE PRESS
Citation statistics
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/24951
Collection中国科学院自动化研究所
Corresponding AuthorZhao, Chen-Ping
Affiliation1.Xidian Univ, Sch Math & Stat, Xian 710126, Shaanxi, Peoples R China
2.Henan Inst Sci & Technol, Sch Math Sci, Xinxiang 453003, Peoples R China
3.Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China
4.Univ Chinese Acad Sci, Sch Comp & Control Engn, Beijing 100190, Peoples R China
5.Beijing Visyst Co Ltd, Res Ctr, Beijing 100190, Peoples R China
Recommended Citation
GB/T 7714
Feng, Xiang-Chu,Zhao, Chen-Ping,Peng, Si-Long,et al. Plug-and-Play Based Optimization Algorithm for New Crime Density Estimation[J]. JOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY,2019,34(2):476-493.
APA Feng, Xiang-Chu,Zhao, Chen-Ping,Peng, Si-Long,Hu, Xi-Yuan,&Ouyang, Zhao-Wei.(2019).Plug-and-Play Based Optimization Algorithm for New Crime Density Estimation.JOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY,34(2),476-493.
MLA Feng, Xiang-Chu,et al."Plug-and-Play Based Optimization Algorithm for New Crime Density Estimation".JOURNAL OF COMPUTER SCIENCE AND TECHNOLOGY 34.2(2019):476-493.
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