title: 3D/2D Model-to-Image Registration for Quantitative Dietary Assessment.
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.
authors.affiliation: Department of Computer Science and Information Engineering, National Cheng Kung University, Taiwan, R.O.C ; Department of Neurosurgery, University of Pittsburgh, Pittsburgh, PA 15213, USA.
authors.forename: Hsin-Chen
authors.initials: HC
authors.lastname: Chen
authors.affiliation: Department of Neurosurgery, University of Pittsburgh, Pittsburgh, PA 15213, USA.
authors.forename: Wenyan
authors.initials: W
authors.lastname: Jia
authors.affiliation: Department of Neurosurgery, University of Pittsburgh, Pittsburgh, PA 15213, USA ; School of Computer Science and Technology, Harbin Institute of Technology, China.
authors.forename: Zhaoxin
authors.initials: Z
authors.lastname: Li
authors.affiliation: Department of Computer Science and Information Engineering, National Cheng Kung University, Taiwan, R.O.C.
authors.forename: Yung-Nien
authors.initials: YN
authors.lastname: Sun
authors.affiliation: Department of Neurosurgery, University of Pittsburgh, Pittsburgh, PA 15213, USA ; Department of Electrical & Computer Engineering, University of Pittsburgh, Pittsburgh, PA 15213, USA.
authors.forename: Mingui
authors.initials: M
authors.lastname: Sun