By a News Reporter-Staff News Editor at NewsRx Law -- Investigators publish new report on Pattern Analysis. According to news reporting from Shaanxi, People’s Republic of China, by NewsRx journalists, research stated, “Exemplar-based face sketch synthesis plays an important role in both digital entertainment and law enforcement. It generally consists of two parts: neighbor selection and recognition weight representation.”
The news correspondents obtained a quote from the research from Xidian University, “In this paper, we proposed a simple but effective method which employs offline random sampling instead of K-NN used in state-of-the-art methods. The proposed random sampling strategy reduces the time consuming for synthesis and has stronger scalability than state-of-the-art methods. In addition, we introduced locality constraint to model the distinct correlations between the test patch and random sampled patches. Extensive experiments on public face sketch databases demonstrate the superiority of the proposed method in comparison to state-of-the-art methods, in terms of both synthesis quality and time consumption. The proposed method could be extended to other heterogeneous face image transformation problems such as face hallucination.”
According to the news reporters, the research concluded: “We release the source codes of our proposed methods and the evaluation metrics for future study online: http://www.ihitworld.com/RSLCR.html.”
For more information on this research see: Random sampling for fast face sketch synthesis. Pattern Recognition , 2018;76():215-227. Pattern Recognition can be contacted at: Elsevier Sci Ltd, The Boulevard, Langford Lane, Kidlington, Oxford OX5 1GB, Oxon, England. (Elsevier - www.elsevier.com; Pattern Recognition - http://www.journals.elsevier.com/pattern-recognition/)
Our news journalists report that additional information may be obtained by contacting N.N. Wang, Xidian Univ, Sch Telecommun Engn, State Key Lab Integrated Serv Networks, Xian 710071, Shaanxi, People’s Republic of China. Additional authors for this research include X.B. Gao and J. Li.
The direct object identifier (DOI) for that additional information is: https://doi.org/10.1016/j.patcog.2017.11.008. This DOI is a link to an online electronic document that is either free or for purchase, and can be your direct source for a journal article and its citation.
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CITATION: (2018-03-15), Recent Findings from Xidian University Has Provided New Information about Pattern Analysis (Random sampling for fast face sketch synthesis), NewsRx Law, 165, ISSN: 0000-0000, BUTTER® ID: 015277729
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