CFP last date
20 May 2024
Call for Paper
June Edition
IJCA solicits high quality original research papers for the upcoming June edition of the journal. The last date of research paper submission is 20 May 2024

Submit your paper
Know more
The week's pick
Responsive image
Enhancing Privacy Preservation: Multi-Attribute Protection with P-Sensitive K-Anonymity

Twinkle Patel Kiran Amin
Random Articles
Reseach Article

Implementation of Real Time Dress-up System based on Image Blending

by Md. Zahangir Alom, Farazul Haque Bhuiyan, Hyo Jong Lee
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 75 - Number 1
Year of Publication: 2013
Authors: Md. Zahangir Alom, Farazul Haque Bhuiyan, Hyo Jong Lee
10.5120/13074-8615

Md. Zahangir Alom, Farazul Haque Bhuiyan, Hyo Jong Lee . Implementation of Real Time Dress-up System based on Image Blending. International Journal of Computer Applications. 75, 1 ( August 2013), 13-23. DOI=10.5120/13074-8615

@article{ 10.5120/13074-8615,
author = { Md. Zahangir Alom, Farazul Haque Bhuiyan, Hyo Jong Lee },
title = { Implementation of Real Time Dress-up System based on Image Blending },
journal = { International Journal of Computer Applications },
issue_date = { August 2013 },
volume = { 75 },
number = { 1 },
month = { August },
year = { 2013 },
issn = { 0975-8887 },
pages = { 13-23 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume75/number1/13074-8615/ },
doi = { 10.5120/13074-8615 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:43:06.787617+05:30
%A Md. Zahangir Alom
%A Farazul Haque Bhuiyan
%A Hyo Jong Lee
%T Implementation of Real Time Dress-up System based on Image Blending
%J International Journal of Computer Applications
%@ 0975-8887
%V 75
%N 1
%P 13-23
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In this paper the real time virtual dress-up system has been proposed. The proposed system consists of multiple tasks including extraction of different body parts, torso detection, resizing input dress images and dress up using blending and re-blending techniques over the subject. The coexistence of different clothing and cluttering backgrounds is the main difficulty for accurate body extraction in image. Haar classifier is applied for detecting face from input frames and geometrical information is used to extract different parts (like a face, a torso, and hands) of a body according to the face position in a frame. Due to the variability of human body, it is complicated to extract accurately. A novel dominant colors based segmentation method is proposed to tackle this problem. First, an image is segmented into uniform areas based on HSV color components. Then, dominant colors of the torso are adaptively selected using color probability model. The torso has been extracted based on the dominant colors to resize the input dress image to fit over the subject body as well as dress size prediction. Automatic dress blending points are calculated on human body using torso starting position and geometrical relationship with face region. A selected dress is scaled and rendered to fit with the subject's body even they move around. Some preprocessing and post processing techniques are used to make outputs more accurate and realistic.

References
  1. Jong-Chul Yoon, In Know Lee and Henry kang published one paper on this topic named "Image–based Dress-up System" in ICUIM- 2011.
  2. Nadia Magnenat-Thalmann, H. Seo, F. Cordier,"Automatic modeling of virtual humans and body clothing", Proc. 3-D Digital imaging and modeling, IEEE Computer Society Press 2003
  3. J. Chai, Jessica K. Hodgins,"Performance animation from low-dimensional control signals", SIGGRAPH 2005
  4. I. Kim, H. Lee, H. Kim,"Magic mirror: A new VR platform design and its applications", ACM SIGCHI International conference on Advances in computer entertainment technology 2004
  5. Karla Peavy Simmons, Body measurement techniques: A comparison of three-dimensional body scanning and physical anthropometric methods, thesis for the degree of Ph. D in North Carolina State University, 2001.
  6. Paquette, S. , Brantley, J. D. , Corner, B. D. , Li, P. , Oliver, T. , Automated extraction of anthropometric data from 3D images, U. S. Army Soldier Biological & Chemical Command, Natick, MA, 1998.
  7. Paquette, S. , 3D scanning in apparel design and human engineering, IEEE Computer Graphics and Applications, 16 (5), 11-15, September, 1996.
  8. Hwang, Su-Jeong, Three dimensional body scanning systems with potential for use in the apparel industry, thesis for the degree of Ph. D in North Carolina State University, 2001.
  9. Hein A. M. Daanen, G. Jeroen van de Water, Whole body scanners, Displays 19(1998) 111- 120.
  10. 3D Scanning methodologies for internationally compatible anthropometric databases, draft international standard ISO/DIS 20685, 2004.
  11. General requirements for establishing an anthropometric database, draft international standard ISO/DIS 15535, 2001.
  12. XinJuan Zhu, Xin Zhang, Jing Qi, Communion system of 3D anthropometric databases based on internet, China Inventing Patent, ZL200510096300. 5.
  13. K. Jeong, S. Jang, J. Chae, G. Cho, and G. Salvendy. 2008. Use of Decision Support for Clothing Products on the Web Results in No Difference in Perception of Tactile Sensation Than Actually Touching the Material, International Journal of Human-Computer Interaction, 24(8), 794-808.
  14. Sun-Young Lee, Jong-Chul Yoon and In-Kwon Lee, 2007, Cartoon-like Video Generation Using Physical Motion Analysis, NPAR 2007 Poster, 2007.
  15. Kenji Hara, Ko Nishino and Katsushi Ikeuchi, 2003, Determining Reflectance and Light Position from a Single Image Without Distant Illumination Assumption, ICCV, Proceedings of the Ninth IEEE International Conference on Computer Vision, Vol 2, p. 560.
  16. Dmitri Bitouk, Neeraj Kumar, Samreen Dhillon, Peter Belhumeur and Shree K. Nayar, 2008, Face Swapping : Automatically replacing faces in photographs, International Conference on Computer Graphics and Interactive Techniques, ACM SIGGRAPH 2008, Article No. 39, p. 1-8.
  17. G. Hua, M. H. Yang, and Y. Wu, Learning to estimate human pose with data. driven belief propagation, Proceedings of international Conference on Computer Vision and Pattern recognition, San Diego, 2005, pp. 747-754.
  18. X. Ren, A. C. Berg, J. Malik, Recovering human body configurations using pair wise constraints between parts, proceedings of International Conference on Computer Vision, eijing, 2005, pp. 8
  19. G. Mori and J. Malik, Estimating human body configurations using shape context matching, In European Conference on Computer Vision, Copenhagen, 2002, pp. 666–680.
  20. G. Mori, X. Ren, A. Efros, and J. Malik, Recovering human body configurations: Combining segmentation and recognition, In Proc. IEEE Conf. on Computer Vision and pattern Recognition, Washington, 2004, pp. 326–333.
  21. P. Viola, M. Jones, Robust real-time face detection, Int. J. computer Vision, 2004, 57(2): pp. 137-154.
  22. Q. X. Ye, W. Gao, W. Q. Wang, and T. J. Huang, A color mage segmentation algorithm by using color and spatial information. Journal of Software, 2004, 15(4): pp. 522-530.
  23. NIST. Anthrokids - anthropometric data of children, http://ovrt. nist. gov/projects/anthrokids/, 1977.
  24. M. W. Lee and I. Cohen, Proposal maps driven MCMC for estimating human body pose in static images. In Proc. IEEE conf. on Computer Vision and Pattern Recognition, Washington, 2004, pp. 334–341.
  25. Most of the database images have been collected from : http://www. abercrombie. com
Index Terms

Computer Science
Information Sciences

Keywords

Torso detection Body measurement Real-time Clothing dress-up system dress color recognition human-computer interaction

Powered by PhDFocusTM