Abstract: A fabric image processing device is provided. The device performs a matting algorithm on the top view image and the side view image to generate a top view silhouette image and a side view silhouette image. The device updates the first neural network model and the first linear regression model according to the top view silhouette image and a physical deformation parameter, and updates the second neural network model and the second linear regression model according to the side view silhouette image and the physical deformation parameter. The device inputs the top view silhouette image and the side view silhouette image to the first neural network model and the second neural network model to generate output vectors. The device concatenates output vectors to generate a concatenated vector, and updates the third linear regression model according to the concatenated vector and the physical deformation parameter.

Abstract: A fabric simulation device and method are provided. The device captures a physical deformation parameters corresponding to a fabric. A fabric specification information includes a fabric category data, a fabric combination data and a fabric weight data. The device generates target-encoding data by conducting a target-encoding algorithm on the fabric category data. The device generates a language processing vector by conducting a natural language processing algorithm on the fabric combination data. The device generates a category vector and a normalized physical deformation parameter by normalize the target-encoding data and the physical deformation parameter, and generate a weight vector by normalize the fabric weight data. The device generate a feature vector by concatenating the category vector, the language processing vector, and the weight vector. The device updates the neural network model according to the feature vector and the normalized physical deformation parameters.