Fractal Evaluation Model of Visual Complexity in Virtual Reality (VR) Shopping Scenes
江 吴 · E-Commerce Letters · 2025
本文围绕VR购物环境中的视觉感知机制，提出一种基于分形维度的评价方法，用于量化场景的视觉复杂度以及和用户场景感知之间的关系，为VR购物环境的设计提供了新的指导方向和操作建议。研究从场景空间布局、商品排列逻辑、背景纹理特征等几方面出发，将虚拟购物场景的视觉感知与分形维度进行关联并建立评价模型。研究发现范围在1.3至1.5的分形维度能有效提升用户对VR购物场景的空间识别效率和情绪舒适度。过高或过低的分形维度会分别导致视觉负荷过载与不足，进而影响决策效率与购买行为。并针对视觉对环境感知的优势和不足，提出主客观评价模型、多因素加权评价模型以及多维度感知评价模型，为提升VR购物体验质量开辟了新的方法路径。This study explores the visual perception mechanisms inherent in virtual reality (VR) shopping environments and presents a fractal dimension-based evaluation method designed to quantify the visual complexity of scenes and its correlation with user perception. This approach offers quantitative tools and operational recommendations for the design of VR shopping experiences. The research investigates various aspects, including the spatial layout of scenes, the logic of product arrangement, and the characteristics of background textures, establishing a relationship between the visual perception of virtual shopping environments and fractal dimensions to formulate an evaluation model. The findings reveal that a fractal dimension within the range of 1.3 to 1.5 significantly enhances users’ spatial recognition efficiency and emotional comfort within VR shopping settings. In contrast, excessively high or low fractal dimensions can lead to visual fatigue and insufficient information, respectively, thereby adversely affecting decision-making efficiency and purchasing behavior. Additionally, in response to the strengths and weaknesses of visual perception in environmental cognition, the study proposes subjective-objective evaluation models, multi-factor weighted evaluation models, and multi-dimensional perception evaluation models, thereby opening up new methodological pathways for enhancing the quality of the VR shopping experience.