TY  - CONF
AU  - Antonio Hernandez
AU  - Nadezhda Zlateva
AU  - Alexander Marinov
AU  - Miguel Reyes
AU  - Petia Radeva
AU  - Dimo Dimov
AU  - Sergio Escalera
A2  - CVPR
PY  - 2012//
TI  - Graph Cuts Optimization for Multi-Limb Human Segmentation in Depth Maps
BT  - 25th IEEE Conference on Computer Vision and Pattern Recognition
SP  - 726
EP  - 732
PB  - IEEE Xplore
N2  - We present a generic framework for object segmentation using depth maps based on Random Forest and Graph-cuts theory, and apply it to the segmentation of human limbs in depth maps. First, from a set of random depth features, Random Forest is used to infer a set of label probabilities for each data sample. This vector of probabilities is used as unary term in α-β swap Graph-cuts algorithm. Moreover, depth of spatio-temporal neighboring data points are used as boundary potentials. Results on a new multi-label human depth data set show high performance in terms of segmentation overlapping of the novel methodology compared to classical approaches.
SN  - 1063-6919
SN  - 978-1-4673-1226-4
L1  - http://refbase.cvc.uab.es/files/HZM2012b.pdf
UR  - http://dx.doi.org/10.1109/CVPR.2012.6247742
N1  - MILAB;HuPBA
ID  - Antonio Hernandez2012
ER  -