期刊
IEEE TRANSACTIONS ON MULTIMEDIA
卷 21, 期 1, 页码 114-123出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TMM.2018.2844087
关键词
Human body shape; model fitting; PCA shape space; depth camera; human pose estimation
3-D human body reconstruction is an important research topic in computer vision. A 3-D human body model can be used in sports science, movie industry and personalized entertainment, especially virtual reality games. Most of depth-based 3-D reconstruction algorithms need multiple cameras surrounding the user and require the user to keep a specific pose strictly while capturing depth images. In this paper, we propose an algorithm to reconstruct the 3-D shape of human bodies using a single commodity depth camera. Our algorithm only needs two depth images of the front-facing and back-facing bodies. It also has strong operability since the proposed method is insensitive to the pose variations between the two depth images. We reconstruct 3-D shapes of front-facing and back-facing bodies from the two depth images, respectively, and stitch them together. We also propose a novel registration method, namely, iterative mid-distance points, which has fast convergence and robustness to the depth noise. The proposed method enables robust and easy-to-use human body reconstruction, and achieves higher accuracy than state-of-the-art methods.
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