DocumentCode :
2829625
Title :
Clothing segmentation and recoloring using background subtraction and back projection method
Author :
Yao, Susu ; Khan, Ishtiaq Rasool ; Farbiz, Farzam
Author_Institution :
Inst. for Infocomm Res., A*STAR, Singapore, Singapore
fYear :
2011
fDate :
11-14 Sept. 2011
Firstpage :
3137
Lastpage :
3140
Abstract :
This paper proposes a new method to automatically segment and re-color the clothing in an image sequence. Background and foreground are separated using background subtraction method with a Gaussian mixture model built for the static scene. Skin and face areas are detected and removed on the segmented foreground. A 2D histogram is constructed using the remaining pixels to model the probability distribution of the clothing chromaticity, which is then applied to each frame to find accurate clothing area using back projection method. The segmented clothing area is re-colored by mapping the hue value to a new one in the HSV color space to maintain the contrast of the clothing. Experiments on the real video captured with a monocular webcam are shown to demonstrate the effectiveness of the proposed algorithm for clothing segmentation and re-coloring.
Keywords :
Gaussian processes; clothing; image colour analysis; image segmentation; image sequences; statistical distributions; video cameras; video signal processing; 2D histogram; Gaussian mixture model; HSV color space; back projection method; background subtraction method; clothing chromaticity; clothing recoloring; clothing segmentation; face area detection; foreground segmentation; image sequence; monocular webcam; probability distribution; skin area detection; static scene; Adaptation models; Clothing; Computational modeling; Histograms; Image color analysis; Image segmentation; Skin; Image segmentation; back-projection; background subtractions; clothing segmentation; image re-coloring;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image Processing (ICIP), 2011 18th IEEE International Conference on
Conference_Location :
Brussels
ISSN :
1522-4880
Print_ISBN :
978-1-4577-1304-0
Electronic_ISBN :
1522-4880
Type :
conf
DOI :
10.1109/ICIP.2011.6116331
Filename :
6116331
Link To Document :
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