文献类型：期刊文献

英文题名：Creating a Computable Cognitive Model of Visual Aesthetics for Automatic Aesthetics Evaluation of Robotic Dance Poses

作者：Peng, Hua[1,2,3];Li, Jing[4];Hu, Huosheng[3];Hu, Keli[1];Tang, Chao[5];Ding, Yulong[6]

机构：[1]Shaoxing Univ, Dept Comp Sci & Engn, Shaoxing 312000, Peoples R China;[2]Jishou Univ, Coll Informat Sci & Engn, Jishou 416000, Peoples R China;[3]Univ Essex, Sch Comp Sci & Elect Engn, Colchester CO4 3SQ, Essex, England;[4]Shaoxing Univ, Acad Arts, Shaoxing 312000, Peoples R China;[5]Hefei Univ, Dept Comp Sci & Technol, Hefei 230601, Peoples R China;[6]Beijing Inst Technol, Sch Automat, Beijing 100081, Peoples R China

年份：2020

卷号：12

期号：1

外文期刊名：SYMMETRY-BASEL

收录：SCI-EXPANDED(收录号：WOS:000516823700023)、、Scopus(收录号：2-s2.0-85079689141)、WOS

基金：This work was financially supported by National Natural Science Foundation of China (Grant No. 61662025, 61871289), and the Research Foundation of Philosophy and Social Science of Hunan Province (Grant No. 16YBX042), and the Natural Science Foundation of Zhejiang Province (Grant No. LY20F030006, LY20F020011), and the Research Foundation of Education Bureau of Hunan Province (Grant No. 16C1311).

语种：英文

外文关键词：robotic dance pose; automatic aesthetics estimation; visual aesthetic cognition; machine learning

外文摘要：Inspired by human dancers who can evaluate the aesthetics of their own dance poses through mirror observation, this paper presents a corresponding mechanism for robots to improve their cognitive and autonomous abilities. Essentially, the proposed mechanism is a brain-like intelligent system that is symmetrical to the visual cognitive nervous system of the human brain. Specifically, a computable cognitive model of visual aesthetics is developed using the two important aesthetic cognitive neural models of the human brain, which is then applied in the automatic aesthetics evaluation of robotic dance poses. Three kinds of features (color, shape and orientation) are extracted in a manner similar to the visual feature elements extracted by human brains. After applying machine learning methods in different feature combinations, machine aesthetics models are built for automatic evaluation of robotic dance poses. The simulation results show that our approach can process visual information effectively by cognitive computation, and achieved a very good evaluation performance of automatic aesthetics.