Vision-based food nutrition estimation via RGB-D fusion network

doi:10.1016/j.foodchem.2023.136309

	Vision-based food nutrition estimation via RGB-D fusion network
	Shao, Wenjing 1; Min, Weiqing 2,3; Hou, Sujuan 1; Luo, Mengjiang 2,3; Li, Tianhao 2,3; Zheng, Yuanjie 1; Jiang, Shuqiang 2,3
	2023-10-30
发表期刊	FOOD CHEMISTRY
ISSN	0308-8146
卷号	424 页码:10
摘要	With the development of deep learning technology, vision-based food nutrition estimation is gradually entering the public view for its advantage in accuracy and efficiency. In this paper, we designed one RGB-D fusion network, which integrated multimodal feature fusion (MMFF) and multi-scale fusion for visioin-based nutrition assessment. MMFF performed effective feature fusion by a balanced feature pyramid and convolutional block attention module. Multi-scale fusion fused different resolution features through feature pyramid network. Both enhanced feature representation to improve the performance of the model. Compared with state-of-the-art methods, the mean value of the percentage mean absolute error (PMAE) for our method reached 18.5%. The PMAE of calories and mass reached 15.0% and 10.8% via the RGB-D fusion network, improved by 3.8% and 8.1%, respectively. Furthermore, this study visualized the estimation results of four nutrients and verified the validity of the method. This research contributed to the development of automated food nutrient analysis (Code and models can be found at http://123.57.42.89/codes/RGB-DNet/nutrition.html).
关键词	Food nutrient Nutrition estimation Food composition Deep learning RGB-D fusion
DOI	10.1016/j.foodchem.2023.136309
收录类别	SCI
语种	英语
资助项目	National Nature Science Foundation of China[62072289] ; National Nature Science Foundation of China[61972378] ; National Nature Science Foundation of China[U19B2040] ; National Nature Science Foundation of China[62125207] ; CAAI-Huawei MindSpore Open Fund
WOS研究方向	Chemistry ; Food Science & Technology ; Nutrition & Dietetics
WOS类目	Chemistry, Applied ; Food Science & Technology ; Nutrition & Dietetics
WOS记录号	WOS:001002350200001
出版者	ELSEVIER SCI LTD
引用统计	被引频次：9[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/21470
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Min, Weiqing; Hou, Sujuan
作者单位	1.Shandong Normal Univ, Sch Informat Sci & Engn, Jinan 250358, Shandong, Peoples R China 2.Chinese Acad Sci, Inst Comp Technol, Key Lab Intelligent Informat Proc, Beijing 100190, Peoples R China 3.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
推荐引用方式 GB/T 7714	Shao, Wenjing,Min, Weiqing,Hou, Sujuan,et al. Vision-based food nutrition estimation via RGB-D fusion network[J]. FOOD CHEMISTRY,2023,424:10.
APA	Shao, Wenjing.,Min, Weiqing.,Hou, Sujuan.,Luo, Mengjiang.,Li, Tianhao.,...&Jiang, Shuqiang.(2023).Vision-based food nutrition estimation via RGB-D fusion network.FOOD CHEMISTRY,424,10.
MLA	Shao, Wenjing,et al."Vision-based food nutrition estimation via RGB-D fusion network".FOOD CHEMISTRY 424(2023):10.