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Content Provider | IEEE Xplore Digital Library |
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Author | Peng Guan Weiss, Alexander Balan, Alexandru O. Black, Michael J. |
Copyright Year | 2009 |
Description | Author affiliation: Department of Computer Science, Brown University, Providence, RI 02912, USA (Peng Guan; Weiss, Alexander; Balan, Alexandru O.; Black, Michael J.) |
Abstract | We describe a solution to the challenging problem of estimating human body shape from a single photograph or painting. Our approach computes shape and pose parameters of a 3D human body model directly from monocular image cues and advances the state of the art in several directions. First, given a user-supplied estimate of the subject's height and a few clicked points on the body we estimate an initial 3D articulated body pose and shape. Second, using this initial guess we generate a tri-map of regions inside, outside and on the boundary of the human, which is used to segment the image using graph cuts. Third, we learn a low-dimensional linear model of human shape in which variations due to height are concentrated along a single dimension, enabling height-constrained estimation of body shape. Fourth, we formulate the problem of parametric human shape from shading. We estimate the body pose, shape and reflectance as well as the scene lighting that produces a synthesized body that robustly matches the image evidence. Quantitative experiments demonstrate how smooth shading provides powerful constraints on human shape. We further demonstrate a novel application in which we extract 3D human models from archival photographs and paintings. |
Starting Page | 1381 |
Ending Page | 1388 |
File Size | 2222421 |
Page Count | 8 |
File Format | |
ISBN | 9781424444205 |
ISSN | 15505499 |
DOI | 10.1109/ICCV.2009.5459300 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2009-09-29 |
Publisher Place | Japan |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Humans Shape |
Content Type | Text |
Resource Type | Article |
Subject | Computer Vision and Pattern Recognition Software |
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