Title :
Interactive Clothing Image Segmentation Based on Superpixels and Graph Cuts
Author_Institution :
Sch. of Comput., Guangxi Univ. of Sci. & Technol., Liuzhou, China
Abstract :
In this paper, we propose an interactive clothing image segmentation method based on super pixels and Graph Cuts. Firstly, we process the image from pixels to super pixels with the method of SLIC to reduce the computational loads and lower the effect of noise, and then a graph is constructed using super pixels as nodes. Finally, min-cut/max-flow algorithm is applied to solve the energy function. In this process, the seeds of clothing or non-clothing are decided interactively. Some given samples show that the method can achieve promising clothing segmentation results.
Keywords :
graph theory; image segmentation; pattern clustering; SLIC method; energy function; graph cuts; interactive clothing image segmentation; min-cut-max-flow algorithm; noise effect; simple linear iterative clustering; superpixels; Clothing; Clustering algorithms; Computer vision; Computers; Image color analysis; Image segmentation; Vectors; Graph Cuts; SLIC; clothing segmentation; interactive image segmentation;
Conference_Titel :
Computer Sciences and Applications (CSA), 2013 International Conference on
Conference_Location :
Wuhan
DOI :
10.1109/CSA.2013.160