| 摘要: |
| 目的 针对传统的产品形态设计与用户视觉认知之间因缺乏关联而产生设计代沟的问题，提出一种基于视觉认知理论、结合眼动追踪技术的产品形态优化设计方法。方法 首先，运用形态分析法提取产品的形态设计要素；其次，基于眼动追踪实验获取视觉形态的眼动认知数据；接着，采用单因素分析法，筛选与形态高度关联的眼动指标；最后，应用数量化Ｉ类理论对设计要素进行参数化编码，通过数据挖掘技术建立眼动追踪指标与设计要素的关系模型。结果 最终得出眼动追踪指标与设计要素的关系模型，继而提炼出与用户视觉认知关联紧密的形态设计要素及其权重排序，从而确定出形态设计的优选方案，并以电热水壶为例，验证了方法的可行性。结论 建立眼动追踪指标与形态设计要素关联的优化设计方法，能够帮助设计师从用户视觉认知的视角优化产品形态，从而提升设计的科学性和合理性。 |
| 关键词: 视觉认知 眼动追踪 设计要素 数据挖掘 关系模型 |
| DOI：10.19554/j.cnki.1001-3563.2019.08.003 |
| 分类号:TB472 |
| 基金项目:国家自然科学基金资助项目(51865003，51465007) |
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| Product Shape Optimization Design Method Based on Visual Cognition Theory |
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LIN Li, GAO Yun-kun, YANG Ming-qing, JIANG Qi, WANG Mei-chao
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Guizhou University, Guiyang 550025, China
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| Abstract: |
| The work aims to propose a product shape optimization design method based on visual cognition theory and combined with eye tracking technology for solving the problem of design generation gap caused by the lack of correlation between traditional product form design and user visual cognition. First, the morphological analysis method was used to extract the design elements of the product form. Secondly, the eye movement cognition data of the visual form was obtained based on the eye tracking experiment. Then, the eye movement index highly correlated with the morphology was screened by the univariate analysis method. Quantitative I-class theory was applied to parameterize the design elements, and establish a relationship model between eye tracking indicators and design elements through data mining technology. Finally, the relationship model between eye tracking index and design elements was obtained, and then the morphological design elements closely related to the user's visual cognition and their weight ordering were extracted to determine the preferred scheme of morphological design. Taking the electric kettle as an example, the feasibility of the method was verified. The optimization design method based on the eye tracking index and the morphological design elements can help the designer to optimize the product form from the perspective of visual cognition, thereby improving the scientific and rational design. |
| Key words: visual cognition eye tracking design element data mining relational model |
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