TY  - CONF
AU  - Eloi Puertas
AU  - Miguel Angel Bautista
AU  - Daniel Sanchez
AU  - Sergio Escalera
AU  - Oriol Pujol
A2  - ECCVW
PY  - 2014//
TI  - Learning to Segment Humans by Stacking their Body Parts,
T2  - LNCS
BT  - ECCV Workshop on ChaLearn Looking at People
SP  - 685
EP  - 697
VL  - 8925
KW  - Human body segmentation
KW  - Stacked Sequential Learning
N2  - Human segmentation in still images is a complex task due to the wide range of body poses and drastic changes in environmental conditions. Usually, human body segmentation is treated in a two-stage fashion. First, a human body part detection step is performed, and then, human part detections are used as prior knowledge to be optimized by segmentation strategies. In this paper, we present a two-stage scheme based on Multi-Scale Stacked Sequential Learning (MSSL). We define an extended feature set by stacking a multi-scale decomposition of bodypart likelihood maps. These likelihood maps are obtained in a first stageby means of a ECOC ensemble of soft body part detectors. In a second stage, contextual relations of part predictions are learnt by a binary classifier, obtaining an accurate body confidence map. The obtained confidence map is fed to a graph cut optimization procedure to obtain the final segmentation. Results show improved segmentation when MSSL is included in the human segmentation pipeline.
L1  - http://refbase.cvc.uab.es/files/PBS2014.pdf
UR  - http://dx.doi.org/10.1007/978-3-319-16178-5_48
N1  - HuPBA;MILAB
ID  - Eloi Puertas2014
ER  -