Fabric classification research has been widely used in the field of fabric production, clothing design and so on. This paper introduced a novel method combining fabric force model, the multi-frame timing information with GCN for fabric classification. This method used 30 different fabrics' moving videos with the wind driving as the experimental datasets. Firstly, it took each frame of the video as a graph node, and then according to the video sequence connectioned for the similar fabric edge nodes. Secondly, it used the fabric force model to preprocess the original video image to extract force flow features as visual words and store them, then used the visual words to explore the potential connections between similar and different types of fabrics, so as to transform the Euclidean fabric video data into non-Euclidean fabric graph structured data. Finally, these data processed by GCN network. This work has a good performance without the effectiveness of light, texture and color, breaks through the limitation that traditional classification method can only classify a few fabrics, and has good classification effect.

[2021-05-05] Printed Article /doc/2020.05.0152/v2