Semantic annotation of national cultural patterns based on dictionary learning
Haiying Zhao, Hong Chen, Gengyun Jia, Zheng Qiao, Shaojie Wang · Scientia Sinica Informationis · 2019
The national cultural pattern is a precious treasure of the Chinese nation. Semantic annotation and analysis of national cultural pattern is useful in cultural heritage and modern recreation. This article presents a multi-label dictionary learning algorithm called similar coefficient multi-label incoherent dictionary learning (SCMIDL) based on a multi-class dictionary learning algorithm. SCMIDL combines the incoherence of the dictionary and the similarity of coefficients, which significantly improves the performance of multi-label annotation. The superior annotation ability of the algorithm was confirmed on three kinds of national cultural pattern datasets constructed for evaluation purposes.