02093nas a2200349   4500000000100000000000100001008004100002260005900043653003400102653003100136653001800167653002500185653002200210653002000232653002400252653002500276653002100301653002200322653001800344653001800362653001800380100001600398700001300414700001600427700002200443245010000465856016100565300001200726490001500738520094800753020004201701       2018                            d  bInstitute of Electrical and Electronics Engineers Inc.10aIntangible cultural heritages10aHuman computer interaction10amixed reality10aCommunity engagement10aInteractive media10aCommunity group10aEmbodied experience10aheritage communities10ainquiring making10amedieval heritage10amixed reality10amulti-sensory10amulti-sensory1 aSimon Bowen1 aTim Shaw1 aJohn Bowers1 aMagnus Williamson00aIlluminations : Exploring Community Engagement with Intangible Heritage Through Multiple Making  uhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85072383287&doi=10.1109%2fDigitalHeritage.2018.8810050&partnerID=40&md5=4ec6ea35ee388d98d54ff5330c126d55  a135-1420 v10735 LNCS3 aWe present an image stylization method to simulate a graceful Chinese art—Random-needle Embroidery designated as Intangible Cultural Heritage. We first develop an effective way to simulate a single thread, and define rendering primitive called stitch which is a collection of threads arranged in a certain pattern. Then, we segment the input image and partition each region into non-uniform sub-regions, from which a color quantization method is proposed to select colors used in the rendering process for each sub-region from a specific color library. During runtime, new stitches can be synthesized for each sub-region via sparse modeling based on the pre-defined stitches. Smoothness constraints are added to this process to avoid local distortions. Finally, rendering image is generated by placing stitches with different attributes on the canvas. Experiments show that our method can perform fine images with the style of random-needle.  a03029743 (ISSN); 9783319773797 (ISBN)