Please use this identifier to cite or link to this item:
http://hdl.handle.net/2445/152533
Title: | GrabCut-Based Human Segmentation in Video Sequences |
Author: | Hernández-Vela, Antonio Reyes Estany, Miguel Ponce López, Víctor Escalera Guerrero, Sergio |
Keywords: | Postura humana Algorismes computacionals Camps aleatoris Posture Computer algorithms Random fields |
Issue Date: | 9-Nov-2012 |
Publisher: | MDPI |
Abstract: | In this paper, we present a fully-automatic Spatio-Temporal GrabCut human segmentation methodology that combines tracking and segmentation. GrabCut initialization is performed by a HOG-based subject detection, face detection, and skin color model. Spatial information is included by Mean Shift clustering whereas temporal coherence is considered by the historical of Gaussian Mixture Models. Moreover, full face and pose recovery is obtained by combining human segmentation with Active Appearance Models and Conditional Random Fields. Results over public datasets and in a new Human Limb dataset show a robust segmentation and recovery of both face and pose using the presented methodology. |
Note: | Reproducció del document publicat a: https://doi.org/10.3390/s121115376 |
It is part of: | Sensors, 2012, vol. 12, num. 11, p. 15377-15393 |
URI: | http://hdl.handle.net/2445/152533 |
Related resource: | https://doi.org/10.3390/s121115376 |
ISSN: | 1424-8220 |
Appears in Collections: | Articles publicats en revistes (Matemàtiques i Informàtica) |
Files in This Item:
File | Description | Size | Format | |
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618863.pdf | 1.52 MB | Adobe PDF | View/Open |
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