TY  - JOUR
AU  - Antonio Hernandez
AU  - Miguel Reyes
AU  - Victor Ponce
AU  - Sergio Escalera
PY  - 2012//
TI  - GrabCut-Based Human Segmentation in Video Sequences
T2  - SENS
JO  - Sensors
SP  - 15376
EP  - 15393
VL  - 12
IS  - 11
KW  - segmentation
KW  - human pose recovery
KW  - GrabCut
KW  - GraphCut
KW  - Active Appearance Models
KW  - Conditional Random Field
N2  - 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.
L1  - http://refbase.cvc.uab.es/files/HRP2012.pdf
UR  - http://dx.doi.org/10.3390/s121115376
N1  - HuPBA;MILAB
ID  - Antonio Hernandez2012
ER  -