Please use this identifier to cite or link to this item:
https://hdl.handle.net/2440/2377
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Type: | Journal article |
Title: | Segmentation of the face and hands in sign language video sequences using color and motion cues |
Author: | Habili, N. Lim, C. Moini, A. |
Citation: | IEEE Transactions on Circuits and Systems for Video Technology, 2004; 14(8):1086-1097 |
Publisher: | IEEE-Inst Electrical Electronics Engineers Inc |
Issue Date: | 2004 |
ISSN: | 1051-8215 |
Statement of Responsibility: | Nariman Habili, Cheng Chew Lim, and Alireza Moini |
Abstract: | We present a hand and face segmentation methodology using color and motion cues for the content-based representation of sign language video sequences. The methodology consists of three stages: skin-color segmentation; change detection; face and hand segmentation mask generation. In skin-color segmentation, a universal color-model is derived and image pixels are classified as skin or nonskin based on their Mahalanobis distance. We derive a segmentation threshold for the classifier. The aim of change detection is to localize moving objects in a video sequences. The change detection technique is based on the F test and block-based motion estimation. Finally, the results from skin-color segmentation and change detection are analyzed to segment the face and hands. The performance of the algorithm is illustrated by simulations carried out on standard test sequences. |
Keywords: | Change detection sign language skin-color segmentation video segmentation |
Description: | Copyright © 2004 IEEE |
DOI: | 10.1109/TCSVT.2004.831970 |
Published version: | http://dx.doi.org/10.1109/tcsvt.2004.831970 |
Appears in Collections: | Aurora harvest 6 Electrical and Electronic Engineering publications |
Files in This Item:
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hdl_2377.pdf | 1.57 MB | Publisher's PDF | View/Open |
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