MOA: Efficient Scene-aware Multi-object Arrangement in VR

3D multi-object arrangement is a fundamental task in VR that relies on accurate and natural initial selection alongside rapid and convenient subsequent manipulation to ensure high efficiency. However, existing methods fail to support efficient multi-object arrangement in highly occluded scenes with densely packed candidate objects through controller-free natural interactions. In this paper, we propose an efficient, scene-aware multi object arrangement method (MOA) designed for fast, precise, and convenient object arrangement. First, MOA introduces an importance-driven multi-object initial selection algorithm that assigns higher spatiotemporally correlated object importance (IMP) to target objects, establishing a natural multi-object initial selection mode that enables quick and accurate selection of high IMP objects. Subsequently, it presents an auxiliary-structure guided multi-object manipulation algorithm that constructs an auxiliary manipulation structure to assist subsequent multi-object manipulation, alongside a multi-modal interaction mode that facilitates swift and natural manipulation. Compared to state of-the-art controller-free and controller-based methods, MOA significantly improves task performance, reduces task load, and enhances convenience in complex multi-object arrangement scenes involving hundreds of highly occluded objects need to be arranged.