Yuanyuan Liu
ABSTRACT
Accurate estimation of food volume is critical in the medical field. However, estimating food volume is a challenging task due to the diverse nature of food, multi-scale and other characteristics. In this paper, we explore the relationship between the properties and volume of the object (food and reference) in the image. By combining Faster R-CNN, Grabcut, Median filtering, and CNN algorithm, we propose a framework for estimating food volume based on reference. The framework uses a front view which contains reference and food to estimate food volume and is applied to image datasets for 5 kinds of foods. The experimental results show the effective performance of this method for predicting volume, and the mean absolute error of each kind of food is less than 4.5%, which shows the model is robust to estimate volume for irregular food.
- Ying Zhou, and Xiaolin Lv. The effect of dietary nutrition intervention in the nursing of patients with nephrotic syndrome [J]. Journal of Clinic Nursing's Practicality, 2017, 2(25):59+61.Google Scholar
- Wang Xuan. How to choose fruits for diabetic patients [J]. New rural technology, 2018 (7).Google Scholar
- Xu Min, Zhao Hui-li and ZHANG Yi-zhi. Practice of continuing diet nursing for 56 post-operative esophageal cancer patients[ J]. Chinese Journal of Nursing, 2016, 51(4):400--403.Google Scholar
- Puri M, Zhu Z, Yu Q, et al. Recognition and volume estimation of food intake using a mobile device[C]// IEEE Workshop on Applications of Computer Vision (WACV 2009), 7-8 December, 2009, Snowbird, UT, USA. IEEE, 2009.Google Scholar
- Myers A, Johnston N, Rathod V, et al. Im2Calories: Towards an Automated Mobile Vision Food Diary[C]// 2015 IEEE International Conference on Computer Vision (ICCV). IEEE, 2016.Google Scholar
- Ren S, He K, Girshick R, et al. Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks[J]. 2015.Google Scholar
- Y. LeCun, L. Bottou, Y. Bengio, and P. Haffner. Gradient-based learning applied to document recognition. Proceedings of the IEEE, noember 1998.Google ScholarCross Ref
- Szegedy C, Liu W, Jia Y, et al. Going Deeper with Convolutions[J]. 2014.Google Scholar
- K. Simonyan and A. Zisserman," Very deep convolutional networks for large-scale image recognition, " in International Conference on Learning Representations, May 2015.Google Scholar
- Girshick R, Donahue J, Darrell T, et al. Rich feature hierarchies for accurate object detection and semantic segmentation[J]. 2013.Google Scholar
- Girshick, Ross. "Fast R-CNN." IEEE International Conference on Computer Vision 2015.Google Scholar
- Boykov Y Y, Jolly M P. Interactive Graph Cuts for Optimal Boundary and Region Segmentation of Objects in N-D Images[J]. Iccv, 2001, 1:105--112.Google Scholar
- Tang M, Gorelick L, Veksler O, et al. GrabCut in One Cut[C]// IEEE International Conference on Computer Vision. IEEE, 2014.Google Scholar
- Zhou W, Zhang D. Progressive Switching Median Filter For The Removal Of Impulse Noise From Highly Corrupted Images[J]. IEEE Trans.cricuits & Syst.ii, 1999, 46(1):78--80.Google ScholarCross Ref
- Dehais J, Anthimopoulos M, Shevchik S, et al. Two-View 3D Reconstruction for Food Volume Estimation[J]. IEEE Transactions on Multimedia, 2017, 19(5):1090--1099.Google ScholarDigital Library
Index Terms
- Food Volume Estimation Based on Reference
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