Research Repository

Feature fusion based automatic aesthetics evaluation of robotic dance poses

Peng, Hua and Li, Jing and Hu, Huosheng and Zhao, Liping and Feng, Sheng and Hu, Keli (2019) 'Feature fusion based automatic aesthetics evaluation of robotic dance poses.' Robotics and Autonomous Systems, 111. 99 - 109. ISSN 0921-8890

Full text not available from this repository. (Request a copy)

Abstract

Inspired by human dancers who make a comprehensive aesthetic judgement of their own dance poses by using both visual and non-visual information, this paper presents a novel feature fusion based approach to automatic aesthetics evaluation of robotic dance poses in order to improve the performance of robotic choreography creation. Four kinds of features are extracted, namely kinematic feature, region feature, contour feature, and spatial distribution feature of colour block. Based on different feature combinations, machine learning is deployed to train aesthetics models for the automatic judgement on robotic dance poses. The proposed approach has been implemented on a simulated robot environment, and experimental results are presented to verify its feasibility and good performance.

Item Type: Article
Uncontrolled Keywords: Robotic dance pose, Feature fusion, Machine learning, Automatic aesthetics estimation
Divisions: Faculty of Science and Health > Computer Science and Electronic Engineering, School of
Depositing User: Elements
Date Deposited: 19 Jul 2021 14:43
Last Modified: 19 Jul 2021 14:43
URI: http://repository.essex.ac.uk/id/eprint/27648

Actions (login required)

View Item View Item