3D/2D model-to-image registration for quantitative dietary assessment

Hsin Chen Chen, Wenyan Jia, Zhaoxin Li, Yung Nien Sun, Mingui Sun

Research output: Chapter in Book/Report/Conference proceedingConference contribution

20 Citations (Scopus)

Abstract

Image-based dietary assessment is important for health monitoring and management because it can provide quantitative and objective information, such as food volume, nutrition type, and calorie intake. In this paper, a new framework, 3D/2D model-to-image registration, is presented for estimating food volume from a single-view 2D image containing a reference object (i.e., a circular dining plate). First, the food is segmented from the background image based on Otsu's thresholding and morphological operations. Next, the food volume is obtained from a user-selected, 3D shape model. The position, orientation and scale of the model are optimized by a model-to-image registration process. Then, the circular plate in the image is fitted and its spatial information is used as constraints for solving the registration problem. Our method takes the global contour information of the shape model into account to obtain a reliable food volume estimate. Experimental results using regularly shaped test objects and realistically shaped food models with known volumes both demonstrate the effectiveness of our method.

Original languageEnglish
Title of host publication2012 38th Annual Northeast Bioengineering Conference, NEBEC 2012
Pages95-96
Number of pages2
DOIs
Publication statusPublished - 2012
Event38th Annual Northeast Bioengineering Conference, NEBEC 2012 - Philadelphia, PA, United States
Duration: 2012 Mar 162012 Mar 18

Publication series

Name2012 38th Annual Northeast Bioengineering Conference, NEBEC 2012

Other

Other38th Annual Northeast Bioengineering Conference, NEBEC 2012
CountryUnited States
CityPhiladelphia, PA
Period12-03-1612-03-18

All Science Journal Classification (ASJC) codes

  • Bioengineering

Fingerprint Dive into the research topics of '3D/2D model-to-image registration for quantitative dietary assessment'. Together they form a unique fingerprint.

Cite this