Abstract
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 body part likelihood maps. These likelihood maps are obtained in a first stage by 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.
Originalsprog | Engelsk |
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Titel | Computer Vision - ECCV 2014 Workshops, Proceedings |
Redaktører | Michael M. Bronstein, Carsten Rother, Lourdes Agapito |
Antal sider | 13 |
Forlag | Springer |
Publikationsdato | 2015 |
Sider | 685-697 |
ISBN (Elektronisk) | 9783319161778 |
DOI | |
Status | Udgivet - 2015 |
Udgivet eksternt | Ja |
Begivenhed | 13th European Conference on Computer Vision, ECCV 2014 - Zurich, Schweiz Varighed: 6 sep. 2014 → 12 sep. 2014 |
Konference
Konference | 13th European Conference on Computer Vision, ECCV 2014 |
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Land/Område | Schweiz |
By | Zurich |
Periode | 06/09/2014 → 12/09/2014 |
Sponsor | Adobe, Amazon, Ascending Technologies, Bosch, Disney Research, Facebook, Google, IJAC, iniLabs, Leica, M-tec, Microsoft Research, Mitsubishi Electric, mOBILEYE, NICTA, NVIDIA, OMRON Corporation, Pelican imaging, Qualcomm, Siemens, SUPERFISH, technicolor, University of Adelaide, The University of North Carolina, Toshiba Corporation, Toyota, VIZrt |
Navn | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
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Vol/bind | 8925 |
ISSN | 0302-9743 |
Bibliografisk note
Publisher Copyright:© Springer International Publishing Switzerland 2015.