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张浩然, 张少魁, 孙博远, 林鑫杰, 刘家宏, 陈学斌, 陈境焕, 张松海. 室内数字三维场景评估方法[J]. 计算机辅助设计与图形学学报. DOI: 10.3724/SP.J.1089.2024-00352
引用本文: 张浩然, 张少魁, 孙博远, 林鑫杰, 刘家宏, 陈学斌, 陈境焕, 张松海. 室内数字三维场景评估方法[J]. 计算机辅助设计与图形学学报. DOI: 10.3724/SP.J.1089.2024-00352
Haoran Zhang, Zhang Shaokui, Sun Boyuan, Lin Xinjie, Liu Jiahong, Xuebin Chen, Jinghuan Chen, Zhang Songhai. The Evaluable Measurements for Interior Digital 3D Scenes[J]. Journal of Computer-Aided Design & Computer Graphics. DOI: 10.3724/SP.J.1089.2024-00352
Citation: Haoran Zhang, Zhang Shaokui, Sun Boyuan, Lin Xinjie, Liu Jiahong, Xuebin Chen, Jinghuan Chen, Zhang Songhai. The Evaluable Measurements for Interior Digital 3D Scenes[J]. Journal of Computer-Aided Design & Computer Graphics. DOI: 10.3724/SP.J.1089.2024-00352

室内数字三维场景评估方法

The Evaluable Measurements for Interior Digital 3D Scenes

  • 摘要: 场景生成需要度量指导场景的优化. 由于场景度量以场景优化为目的, 并且度量结果对人类通常较难解释, 缺乏专业室内设计背景的人需要通过场景的定量评估来理解一个房间功能、美学和人因因素的合理性. 文中提出用于自动评估室内三维场景的10项评估指标, 包括功能、美学和人因3个评价维度. 首先, 从场景物件的使用性与功能关联出发, 通过可达性、可见性、开阔度、关联关系和功能比例来衡量场景的功能质量; 其次, 基于场景平面构图和人视点视野, 使用平衡性、齐整度与和谐性度量场景的美学质量; 最后, 根据人类活动模拟, 采用流线合理性和活动舒适度评估人因质量. 所提评估方法能通过分项指标展示输入场景的优缺点, 为场景优化和设计迭代提供参考. 选取3D-Front数据库的50个场景进行对比评估, 实验结果表明, 采用该方法进行室内场景评估的效果与专业设计师水平相当, 二者平均评分差异为0.133~0.220, 且评估结果的有效性受到专业设计师和普通用户的肯定; 在与PlanIT和HAISOR的对比实验中, 基于所提评估方法的场景生成技术在用户评估中获得了更高的功能、美学、人因和总体评分, 在度量场景上更加合理.

     

    Abstract: Scene synthesis needs measurement for optimization. For such measurement is aimed mainly at scene optimization, and measurement results are difficult for human to interpret, people without professional interior design background need quantified evaluation to understand how a room is functionally/aesthetically/ergonomically reasonable. This paper introduces ten metrics for automatic evaluation of interior 3D scenes, comprising three aspects: functionality, aesthetics and ergonomics. First, starting from the usability and functional relationships of scene objects, scene functionality is assessed using accessibility, visibility, clearance, pairwise relationship and functional proportion. Second, considering layout composition and human perspective, scene aesthetics is evaluated by balance, alignment and harmony. Third, based on human activity simulations, ergonomic factors are analyzed by evaluating circulation and activity convenience. The proposed evaluation method can highlight the strengths and weaknesses of input scenes through individual evaluation metrics, aiding in scene optimization and design iteration. A comparison evaluation is conducted on 50 scenes from 3D-Front database, and the experimental results demonstrate that the proposed method for indoor scene evaluation performs at a level comparable to that of professional designers, with an average scoring difference ranging from 0.133 to 0.220. The validity of the evaluation results is confirmed by both professional designers and general users. In comparative experiments with PlanIT and HAISOR, the scene generation technique based on the proposed evaluation method achieves higher scores in functionality, aesthetics, ergonomics and overall evaluation, indicating a more reasonable approach to scene assessment.

     

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