Food volume estimation method based on 3D model nesting

A model estimation and food technology, applied in computing, image data processing, instruments, etc., can solve problems such as improvement, difficulty in use, and unfavorable user experience

Inactive Publication Date: 2018-11-16
BEIJING NORMAL UNIVERSITY
View PDF4 Cites 6 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the currently used method based on contour extraction and model matching nesting requires a lot of user interaction, and the process is cumbersome and not easy to use
More

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Food volume estimation method based on 3D model nesting
  • Food volume estimation method based on 3D model nesting
  • Food volume estimation method based on 3D model nesting

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0018] The present invention will be described in further detail below in conjunction with the accompanying drawings.

[0019] figure 1 It is a flow chart of food volume estimation based on three views with the hand as the reference frame.

[0020] pass below figure 1 The present invention is described in detail as a food volume estimation method based on 3D model nesting.

[0021] Step 1: Through investigation and research in this paper, it is found that most of the cooked food can be nested by several fixed models, especially for weight loss and healthy food. Therefore, this paper selects a certain number of 3D models through statistical analysis to build a 3D model library.

[0022] This paper builds a 3D geometric shape model library. For the cuboid, it can be used to calculate foods such as cheese sticks, the formula is:

[0023] V=l*w*h (1)

[0024] For cylinders, it can be used to calculate food such as burgers, the formula is:

[0025] V=πr 2 *h (2)

[0026] F...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The present invention discloses a food volume estimation method based on 3D model nesting. The method can restore a simple geometric model corresponding to foods so as to solve the estimated volume ofthe foods. The method comprises the following steps of: selecting a special model to establish a three-dimensional model library, and inputting user hand information; putting the hand and the foods to the same plane for shooting to obtain a three-view image; performing L*a*b color space preprocessing of the image, performing k-means clustering segmentation of a processing result, and obtaining animage segmentation result; performing outer contour matching of the segmentation result and the three views of the model in the three-dimensional model library, and according to the special function,calculating the matching degree of the foods and each model projection map to find out a projection map having the maximum matching degree, wherein the three-dimensional model corresponding to the projection map having the maximum matching degree is a three-dimensional model corresponding to the foods; and taking the hand as a measuring scale to determine the parameters of the matching model so as to estimate the volumes of the foods through a volume calculation formula. The food volume estimation method based on 3D model nesting can simplify the volume reconfiguration complexity to estimatethe effect of food volumes.

Description

technical field [0001] The invention belongs to the technical fields of computer image processing and computer vision, and in particular relates to a food volume estimation algorithm based on nested matching of 3D model outlines suitable for mobile APP applications. Background technique [0002] As early as 1997, the World Health Organization (WTO) had listed obesity as a disease. Studies have shown that at the individual level, people can limit their energy intake from total fat and sugar, and increase their consumption of fruits, vegetables, legumes, whole grains, and nuts. It can be seen that diet control has a great effect on the health management of obese patients. With the popularization of smart phones, it is very convenient to use mobile phones to obtain and process photos of edible food. Users can estimate the volume of food and the composition of various nutrients through the APP, so that users can understand the content of various components of the food they eat,...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
IPC IPC(8): G06T7/62G06T7/10
CPCG06T2207/30128G06T7/10G06T7/62
Inventor 郑新宫逸菲姚润雷沁怡尹乾
Owner BEIJING NORMAL UNIVERSITY
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap