Document Type
Article
Publication Date
9-2014
Publication Source
Journal of Computer Science and Technology
Abstract
Human weight estimation is useful in a variety of potential applications, e.g., targeted advertisement, entertainment scenarios and forensic science. However, estimating weight only from color cues is particularly challenging since these cues are quite sensitive to lighting and imaging conditions. In this article, we propose a novel weight estimator based on a single RGB-D image, which utilizes the visual color cues and depth information. Our main contributions are three-fold.
First, we construct the W8-RGBD dataset including RGB-D images of different people with ground truth weight.
Second, the novel sideview shape feature and the feature fusion model are proposed to facilitate weight estimation. Additionally, we consider gender as another important factor for human weight estimation.
Third, we conduct comprehensive experiments using various regression models and feature fusion models on the new weight dataset, and encouraging results are obtained based on the proposed features and models.
Inclusive pages
777–784
ISBN/ISSN
1000-9000
Document Version
Postprint
Copyright
Copyright © 2014, Springer
Publisher
Springer
Volume
29
Peer Reviewed
yes
Issue
5
eCommons Citation
Nguyen, Tam; Feng, Jiashi; and Yan, Shuicheng, "Seeing Human Weight from a Single RGB-D Image" (2014). Computer Science Faculty Publications. 77.
https://ecommons.udayton.edu/cps_fac_pub/77
Included in
Graphics and Human Computer Interfaces Commons, Numerical Analysis and Scientific Computing Commons, Other Computer Sciences Commons
Comments
The document is available for download is the authors' accepted manuscript, provided in compliance with the publisher's policy on self-archiving. Differences may exist between this document and the published version, which is available using the link provided. Permission documentation is on file.