@article{ART003277360},
author={Park Byeongchan and Seyoung Jang and Seok-Yoon Kim and Youngmo Kim},
title={A Metavers Virtual Spaces Congestion Estimation Method for Based on Object-level Pixel Cluster Analysis},
journal={Journal of Software Assessment and Valuation},
issn={2092-8114},
year={2025},
volume={21},
number={4},
pages={133-140}
TY - JOUR
AU - Park Byeongchan
AU - Seyoung Jang
AU - Seok-Yoon Kim
AU - Youngmo Kim
TI - A Metavers Virtual Spaces Congestion Estimation Method for Based on Object-level Pixel Cluster Analysis
JO - Journal of Software Assessment and Valuation
PY - 2025
VL - 21
IS - 4
PB - Korea Software Assessment and Valuation Society
SP - 133
EP - 140
SN - 2092-8114
AB - The increasing number of users in metaverse platforms has heightened the need for real-time monitoring of congestion levels within virtual spaces. Conventional congestion estimation methods rely on simple user counts or location-based density calculations, which are limited in their ability to precisely reflect the actual spatial distribution and arrangement of objects. To address these limitations, this paper proposes a congestion estimation method based on object-level pixel cluster analysis using rendered scene images from metaverse environments. The proposed method consists of four stages: object region extraction, preprocessing, pixel-cluster-based analysis of occupied object areas, and quantitative congestion estimation. This approach enables more accurate reflection of perceived congestion levels by analyzing pixel occupancy ratios and clustering density rather than simple population counts. Therefore, the proposed method is expected to improve user experience and enhance spatial management efficiency in large-scale metaverse environments such as virtual education, performances, exhibitions, and conferences.
KW - Metaverse;Virtual Space;Congestion Estimation;Pixel Occupancy Density;Monitoring
DO -
UR -
ER -
Park Byeongchan, Seyoung Jang, Seok-Yoon Kim and Youngmo Kim. (2025). A Metavers Virtual Spaces Congestion Estimation Method for Based on Object-level Pixel Cluster Analysis. Journal of Software Assessment and Valuation, 21(4), 133-140.
Park Byeongchan, Seyoung Jang, Seok-Yoon Kim and Youngmo Kim. 2025, "A Metavers Virtual Spaces Congestion Estimation Method for Based on Object-level Pixel Cluster Analysis", Journal of Software Assessment and Valuation, vol.21, no.4 pp.133-140.
Park Byeongchan, Seyoung Jang, Seok-Yoon Kim, Youngmo Kim "A Metavers Virtual Spaces Congestion Estimation Method for Based on Object-level Pixel Cluster Analysis" Journal of Software Assessment and Valuation 21.4 pp.133-140 (2025) : 133.
Park Byeongchan, Seyoung Jang, Seok-Yoon Kim, Youngmo Kim. A Metavers Virtual Spaces Congestion Estimation Method for Based on Object-level Pixel Cluster Analysis. 2025; 21(4), 133-140.
Park Byeongchan, Seyoung Jang, Seok-Yoon Kim and Youngmo Kim. "A Metavers Virtual Spaces Congestion Estimation Method for Based on Object-level Pixel Cluster Analysis" Journal of Software Assessment and Valuation 21, no.4 (2025) : 133-140.
Park Byeongchan; Seyoung Jang; Seok-Yoon Kim; Youngmo Kim. A Metavers Virtual Spaces Congestion Estimation Method for Based on Object-level Pixel Cluster Analysis. Journal of Software Assessment and Valuation, 21(4), 133-140.
Park Byeongchan; Seyoung Jang; Seok-Yoon Kim; Youngmo Kim. A Metavers Virtual Spaces Congestion Estimation Method for Based on Object-level Pixel Cluster Analysis. Journal of Software Assessment and Valuation. 2025; 21(4) 133-140.
Park Byeongchan, Seyoung Jang, Seok-Yoon Kim, Youngmo Kim. A Metavers Virtual Spaces Congestion Estimation Method for Based on Object-level Pixel Cluster Analysis. 2025; 21(4), 133-140.
Park Byeongchan, Seyoung Jang, Seok-Yoon Kim and Youngmo Kim. "A Metavers Virtual Spaces Congestion Estimation Method for Based on Object-level Pixel Cluster Analysis" Journal of Software Assessment and Valuation 21, no.4 (2025) : 133-140.
