Minecraft video aesthetics quality assessment model

Name: Hasegawa, Ryosuke

Organization : Ritsumeikan University

Email : is0519hv@ed.ritsumei.ac.jp

Name: Yu, Lian

Organization : Ritsumeikan University

Email : is0487xx@ed.ritsumei.ac.jp

Name: Tanabe, Jun

Organization : Ritsumeikan University

Email : gr0581vv@ed.ritsumei.ac.jp

Name: Thaonmas, Ruck

Organization : Ritsumeikan University

Email : ruck@is.ritsumei.ac.jp

LCSH: Video games -- Aesthetics

LCSH: Computer graphics

LCSH: Image processing

Abstract: We propose the Minecraft Video Aesthetic Quality Assessment Model (MCVQA), a tool designed to assess the aesthetic quality of Minecraft videos (MC videos) comprehensively. We explain the meticulous processes, including creating purpose-built datasets, implementing sophisticated feature extraction techniques, and finetuning model hyperparameters. We validate MCVQA’s efficacy through a two-step approach: accuracy validation and an information recommendation system. In conclusion, first, using the datasets created in this study, an impressive 63.6% alignment was observed between the "best" shot types assigned by the user and the model’s predictions. Subsequently, the usefulness of MCVQA as a recommendation system was validated, and a remarkable accuracy of 58.3% was confirmed.

King Mongkut's University of Technology North Bangkok. Central Library

Address: BANGKOK

Email: library@kmutnb.ac.th

Created: 2023

Modified: 2025-03-04

Issued: 2025-03-04

BibliograpyCitation : In King Mongkut's University of Technology Thonburi. The 13th International Conference on Advances in Information Technology (IAIT 2023) (Article 35). Bangkok : King Mongkut's University of Technology Thonburi

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