01609nas a2200253   4500000000100000000000100001008004100002260007600043653003300119653002500152653001900177653003900196100001700235700001700252700001800269700001100287700001300298245008100311856011800392300001200510490000600522520080700528020002001335       2019                            d  bBulgarian Academy of Sciences, Institute of Mathematics and Informatics10aIntangible cultural heritage10aIdentification model10aImage database10aPecking opera painted faces (popf)1 aGuancan Yang1 aHuilin Zhang1 aXiaomei Zhang1 aYue Yu1 aJie Yang00aDigital Inheritance of POPF Based on Image Database and Identification Model  uhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85084200232&partnerID=40&md5=a9b1da28d144b42636ca2ccb12536e88  a315-3210 v93 aPecking Opera Painted Faces (POPF) is a Chinese intangible cultural heritage full of aesthetic value. However, their cultural connotations become less known in modern society. It is therefor, necessary to make public easily understand unique cultural connotation and aesthetic value of POPF. In this project, we built a POPF image database based on the image classification model, with the aim to better showcase POPF. The images are classified into multiple categories according to the traditional connotation patterns. By using the MLP (Multilayer Perceptrons) algorithm classifier, the classification accuracy of model has approached 70\%. Using those tools, the uncertainty of information about images of POPF can be reduced appreciably, and would benefit the innovation of derivatives around POPF.  a13144006 (ISSN)