Abstract
In this paper, an automatic food volume estimation method based on outer contour matching is proposed, which avoids the complicated calculation. We pre-defined a simple 3D model library and stored the projections and the user’s hand. Users took three images containing their hands from three views. The contour of segmented image was compared with the projections to find the best match. Meanwhile, we took the user’s hand as the scale and calculated the volume. As the method is easy to operate, less space-consuming, it is quite suitable for integrated application in the mobile app.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
World Health Organization, February 2018. Obesity and overweight. http://www.who.int/mediacentre/factsheets/fs311/en/
World Health Organisation, February 2018. Obesity and overweight. http://www.who.int/mediacentre/factsheets/fs311/zh/
Puri, M., Zhu, Z., Yu, Q., Divakaran, A., Sawhney, H.: Recognition and volume estimation of food intake using a mobile device. Sarnoff Corporation (2009)
Jia, W., Yue, Y., Fernstrom, J.D., Zhang, Z., Yang, Y., Sun, M.: 3D localization of circular feature in 2D image and application to food volume estimation. In: 34th Annual International Conference of the IEEE EMBS
Image moment – Wikipedia. https://en.wikipedia.org/wiki/Image_moment
Acknowledgment
The research work described in this paper was fully supported by the grants from the National Natural Science Foundation of China (Project No. 61472043), National Key Research and Development Program Project: “The key technologies research and integrated demonstration of mountain torrent disaster monitoring and early warning (2017YFC1502505). Prof. Xin Zheng and Qian Yin are the authors to whom all correspondence should be addressed.
Author information
Authors and Affiliations
Corresponding authors
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer International Publishing AG, part of Springer Nature
About this paper
Cite this paper
Zheng, X., Gong, Y., Lei, Q., Yao, R., Yin, Q. (2019). Multi-view Model Contour Matching Based Food Volume Estimation. In: Ahram, T. (eds) Advances in Artificial Intelligence, Software and Systems Engineering. AHFE 2018. Advances in Intelligent Systems and Computing, vol 787. Springer, Cham. https://doi.org/10.1007/978-3-319-94229-2_9
Download citation
DOI: https://doi.org/10.1007/978-3-319-94229-2_9
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-94228-5
Online ISBN: 978-3-319-94229-2
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)