Abstract:

Estabishment method and process a smart database designed for women’s clothing silhouettes were proposed to accurately judge the existing women's fashion profile. The first step was to detect the human face from a static figure. Then, the human body was characterized by the maximum  posteriori probability model. Thirdly, the foreground models from the original figures were extracted with the graph cuts algorithm. The final step includes the definition of the key points of the key points of the generalized silhouettes, the measurement of the corresponding dimensions, and the process to archive the data. Intelligent measurement criterion focused on various further presented special cases. Besides, a meaningjul concept pf "drastic change point" was proposed, which was proved important to numerically handle a wider range of women's clothng. This proposed method can be used for effectively measuring 8 majordimensions of women's clothing silhouette from given static images, which could be further applied to estimate the future silhouette trends in the field of fashion design.

Key words: women's clothing, clothing silhouette, silhouette dimension, human body segmentation, smart database