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We address the problem of estimating human pose and body shape from 3D scans over time. Reliable estimation of 3D body shape is necessary for many applications including virtual try-on, health monitoring, and avatar creation for virtual reality. Scanning bodies in minimal clothing, however, presents a practical barrier to these applications. We address this problem by estimating body shape under clothing...
In this paper, we address the problem of temporal alignment of surfaces for subjects dressed in wide clothing, as acquired by calibrated multi-camera systems. Most existing methods solve the alignment by fitting a single surface template to each instant's 3D observations, relying on a dense point-to-point correspondence scheme, e.g. by matching individual surface points based on local geometric features...
We introduce a morph able template for dressed human modeling, called Morph able Dressed Human (MDH) template. The template is obtained by learning basic functions from two common types of clothes (long shirts and trousers) and defining a deform-combine manipulation. Our MDH template is parametric, spans variation in both clothes and body/pose, and can generate various dressed human shapes. The template...
In this paper, we propose a method of recognizing the state of a clothing item by using three-dimensional(3D) data observed from multiple directions in an integrated manner. The situation dealt with in this paper is that a clothing item is observed from different directions by rotating it along a vertical axis. First, sets of 3D points obtained from each observation are integrated on a depth buffer...
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