Scheduled System Maintenance:
Some services will be unavailable Sunday, March 29th through Monday, March 30th. We apologize for the inconvenience.
By Topic

Human body segmentation based on independent component analysis with reference at two-scale superpixel

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $31
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)
Li, S. ; Dept. of Electron. Eng., Dalian Univ. of Technol., Dalian, China ; Lu, H.-C. ; Ruan, X. ; Chen, Y.-W.

In this study, a novel method to segment human body in static image is proposed based on independent component analysis with reference (ICA-R) at two-scale superpixel. In this work, the task is mainly decomposed into torso and lower body recovery. With the detected face, we obtain the reference signal of torso in the coarse torso region estimated by an augmented deformable torso model on the basis of the first-scale superpixel. The hip region is estimated based on the segmented torso for the lower body reference at the second-scale superpixel. Experiments on our dataset show that the proposed approach is robust and can accurately segment human body in images with a variety of poses, backgrounds and clothing.

Published in:

Image Processing, IET  (Volume:6 ,  Issue: 6 )