[Home ] [Archive]   [ فارسی ]  
:: Main :: About :: Current Issue :: Archive :: Search :: Submit :: Contact ::
Main Menu
Home::
Journal Information::
Articles archive::
For Authors::
For Reviewers::
Registration::
Contact us::
Site Facilities::
Publication Statistics::
List of Reviewers::
Social Networks::
::
Search in website

Advanced Search
..
Receive site information
Enter your Email in the following box to receive the site news and information.
..
:: Volume 5, Issue 1 (Vol.5, No.1 2019) ::
2019, 5(1): 83-103 Back to browse issues page
Three-Dimensional Human Pose Estimation from a Single Image Using Non-linear Convolutional Neural Network Based on Shape Information
Faranak Shamsafar , Hossein Ebrahimnezhad *
sahand university of technology , ebrahimnezhad@sut.ac.ir
Abstract:   (10444 Views)

3D human pose estimation is one of the most significant tasks in computer vision with wide range of applications. The works for estimating human pose initialized from 2D skeletal estimation from multiple data and has proceeded toward 3D skeletal estimation from minimum input information. In this paper, 3D human pose estimation from a single RGB image is investigated. The proposed work is considered as the ones which firstly estimate 2D pose and then lift the estimated 2D configuration to 3D space. Since most of the errors in this attitude are originated by inaccurate 2D pose inference, we have proposed a method for predicting more accurate 2D poses to obtain 3D poses with less errors. The proposed approach for estimating 2D pose has leveraged deep learning along with the information of the edge map. In other words, we have made use of edge features, which are hand-designed features, in order to guide the deep neural network in training and in learning the features in accordance with the defined objective. Experimental results have demonstrated less errors in 2D and consequently 3D pose estimation in Human3.6M and HumanEva-I benchmarks.

Keywords: Human pose estimation, Deep learning, Convolutional neural networks, Edge map
Full-Text [PDF 2014 kb]   (2420 Downloads)    
Type of Study: Research | Subject: Machine Vision
Received: 2018/02/5 | Accepted: 2018/08/8 | Published: 2019/01/28
Send email to the article author

Add your comments about this article
Your username or Email:

CAPTCHA


XML   Persian Abstract   Print


Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

shamsafar F, ebrahimnezhad H. Three-Dimensional Human Pose Estimation from a Single Image Using Non-linear Convolutional Neural Network Based on Shape Information. Nonlinear Systems in Electrical Engineering 2019; 5 (1) :83-103
URL: http://journals.sut.ac.ir/jnsee/article-1-179-en.html


Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Volume 5, Issue 1 (Vol.5, No.1 2019) Back to browse issues page
سامانه های غیرخطی در مهندسی برق Journal of Nonlinear Systems in Electrical Engineering
نشریه سامانه‌های غیرخطی در مهندسی برق در خصوص اصول اخلاقی انتشار مقاله، از توصیه‌های «کمیته بین‌المللی اخلاق نشر» موسوم به COPE و «منشور و موازین اخلاق پژوهش» مصوب معاونت پژوهش و فناوری وزارت علوم، تحقیقات و فناوری تبعیت می‌کند.
Persian site map - English site map - Created in 0.05 seconds with 37 queries by YEKTAWEB 4657