Object Cluster Registration of Dissimilar Rooms Using Geometric Spatial Affordance Graph to Generate Shared Virtual Spaces
Seonji Kim, Dooyoung Kim, Jae‐Eun Shin, Woontack Woo
Abstract
We propose Object Cluster Registration (OCR) using Geometric Spatial Affordance Graph (GSAG) to support user interaction with multiple objects in a shared space generated from two dissimilar rooms. Previous research on generating a shared virtual space from dissimilar real spaces has only reflected the information of individual objects and aimed at maximizing the area of the shared space. This led to limited interactions relying on the singular affordances of objects, neglecting to consider the usability and effectiveness of the generated shared spaces. The proposed OCR with GSAG, which considers the relationship between objects based on facing formation, extracts optimal object cluster pairs to align dissimilar rooms in generating shared virtual spaces. In an evaluation study involving 100 multi-cluster space pairs, applying OCR using GSAG showed greater effectiveness in preserving object correlations compared to cases where OCR was not used. Furthermore, the size of the shared space did not significantly differ between the two methods. This suggests that factoring in the relationship between objects does not compromise the objective of maximizing the shared virtual space. The proposed method is expected to serve as a foundation for generating shared virtual spaces that are more user-oriented and efficient by facilitating a wider range of collaborative activities for remote users in dissimilar real spaces with varied configurations.