APPLICATION OF STATISTICAL MODELS TO ESTIMATE PERSONAL TASTES IN TEXTILE DESIGN(International Workshop on Advanced Image Technology 2006)

スポンサーリンク

概要

• 論文の詳細を見る

• Textile design companies should be aware of consumer tastes regarding brand-new designs. Inquiry is the only method available to gather this information. This paper describes a new technique for estimating personal tastes regarding textile design. For machine learning, we apply two statistical models-nonlinear Support Vector Machine (SVM) and linear discriminant function-that learn the relationship between each design's image features and personal tastes and classify the design samples as like or dislike. Processing each textile image yields twelve color and three shape features influencing impressions. We estimate recognition accuracy based on the data comprising twenty-one samples and eleven personal tastes. We select one sample and construct models using the others. The selected sample is classified using the models, and their recognition accuracies are compared. The result indicates that the nonlinear SVM can estimate personal tastes more accurately than the linear discriminant function; their mean recognition rates are 86.4% and 64.1%, respectively.

• 社団法人電子情報通信学会の論文
• 2006-01-03

著者

• Nakatani Kotaro

  Department Of Information And Electronics Technology Research Institute Of Osaka Prefecture

• Kamei Yoshihiro

  Cozy Design

• Moriwaki Kosuke

  Department of Information and Electronics Technology Research Institute of Osaka Prefecture

関連論文

• APPLICATION OF STATISTICAL MODELS TO ESTIMATE PERSONAL TASTES IN TEXTILE DESIGN(International Workshop on Advanced Image Technology 2006)

スポンサーリンク