filename     : Dib16a.pdf
entry        : inproceedings
conference   : European Conference on Computer Vision (ECCV), Amsterdam, the Netherlands, October 8-16, 2016
pages        : 88--104
year         : 2016
month        : October
title        : Shape from Selfies : Human Body Shape Estimation using CCA Regression Forests
subtitle     :
author       : Endri Dibra and Cengiz {\"{O}}ztireli and Remo Ziegler and Markus Gross
booktitle    : Computer Vision - {ECCV} 2016  - 14th European Conference
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editor       : 
publisher    : Springer
publ.place   : 
volume       : 
issue        : 
language     : english
keywords     : human shape estimation, CCA, Random Forests, shape from silhouettes
abstract     : In this work, we revise the problem of human body shape estimation from monocular imagery. Starting from a statistical human shape model that describes a body shape with shape parameters, we describe a novel approach to automatically estimate these parameters from a single input shape silhouette using semi-supervised learning. By utilizing silhouette features that encode local and global properties robust to noise, pose and view changes, and projecting them to lower dimensional spaces obtained through multi-view learning with canonical correlation analysis, we show how regression forests can be used to compute an accurate mapping from the silhouette to the shape parameter space. This results in a very fast, robust and automatic system under mild self-occlusion assumptions. We extensively evaluate our method on thousands of synthetic and real data and compare it to the state-of-art approaches that operate under more restrictive assumptions.