AN IMPRESSION EVALUATION MODEL FOR APPAREL PRODUCT RETRIVAL BASED ON IMAGE ANALYSIS
AN IMPRESSION EVALUATION MODEL FOR APPAREL PRODUCT RETRIVAL BASED ON IMAGE ANALYSIS
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基于图像分析的服装产品检索印象评价模型
DOI：
10.5057/kei.3.11
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发表时间：
2001
期刊：
影响因子：
--
通讯作者：
Hyungsup Kim
中科院分区：
文献类型：
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作者：
H. Park;Eri Koyama;T. Furukawa;M. Takatera;Y. Shimizu;Hyungsup Kim
在本文中，我们提出了一种可用于服装数据检索的印象评估模型。使用引起特定印象并且在连续评估中可再现的印象词，我们开发了一种模型，能够根据通过图像分析提取的服装图像的物理特征来估计印象评估值。这些值用作初始检索数据。利用这些印象词，我们使用语义差异方法来分析受试者对服装图像的印象。我们通过将同一受试者相隔一年进行的两次印象评估结果相关联，确认了“幼稚-成熟”等十对印象词的再现性。采用空间频率分析和彩色图像处理来分析服装图像的色彩空间数据。从结果中，我们获得了三类特征：轮廓、色调和图案。通过回归分析得到组合不同特征的模型系数，生成印象评价模型。六对印象词的评价值与模型F估计值的相关性达到0.7或更高。其中，“女性-男性”对受轮廓特征的影响较大，而包括“艳丽-平淡”在内的其他五对词对受图案特征的影响更大。
In this paper, we propose an impression evaluation model that can be used for retrieval of apparel data. Using impression words which evoke specific impressions and are reproducible in successive evaluations, we developed a model capable of estimating impression evaluation values from the physical features of apparel images extracted through image analysis. These values function as initial retrieval data. Employing these impression words, we used the Semantic Differential method to analyze subjects' impressions of apparel images. We confirmed the reproducibility of ten pairs of impression words such as “childish-mature”by correlating the results of two impression evaluations by the same subjects conducted one year apart. Spatial frequency analysis and color image processing were used to analyze the color space data of apparel images. From the results, we obtained three types of features: silhouette, hue and pattern. The coefficients for models combining different features were obtained through regression analysis to generate impression evaluation models. Evaluation values for six pairs of impression words exhibited a correlation of 0.7 or more with the values estimated by model F. Of these, the “feminine-mannish”pair was highly influenced by thesilhouette feature while five other word pairs including “showy-plain”were more influenced by the pattern feature.