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Creating a Computable Cognitive Model of Visual Aesthetics for Automatic Aesthetics Evaluation of Robotic Dance Poses

Peng, Hua and Li, Jing and Hu, Huosheng and Hu, Keli and Tang, Chao and Ding, Yulong (2019) 'Creating a Computable Cognitive Model of Visual Aesthetics for Automatic Aesthetics Evaluation of Robotic Dance Poses.' Symmetry, 12 (1). ISSN 2073-8994

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Abstract

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.

Item Type: Article
Divisions: Faculty of Science and Health > Computer Science and Electronic Engineering, School of
Depositing User: Elements
Date Deposited: 10 Jun 2020 12:58
Last Modified: 10 Jun 2020 13:15
URI: http://repository.essex.ac.uk/id/eprint/27658

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