Development Of Food Tracking System Using Machine Learning

被引:0
|
作者
Jijesh, J. J. [1 ]
Jinesh, J. J. [2 ]
Bolla, Dileep Reddy [3 ]
Sruthi, P., V [1 ]
Dileep, M. R. [4 ]
Keshavamurthy [5 ]
机构
[1] Sri Venkateshwara Coll Engn, Dept E&CE, Bangalore, Karnataka, India
[2] L&T Technol Serv Ltd, Aerosp, Mysore, Karnataka, India
[3] NITTE Meenakshi Inst Technol, Dept CSE, Bangalore, Karnataka, India
[4] Govt Coll Engn, Dept CSE, Kanpur, Uttar Pradesh, India
[5] Atria Inst Technol, Dept E&CE, Bengaluru, India
关键词
Support Vector Machines (SVM); Calorie measurement; Scale Invariant Feature Transform (SIFT); Speeded Up Robust Features (SURF) Renesas microcontroller;
D O I
10.1109/ICEECCOT52851.2021.9708031
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
The use of technology has played a vital role in the person's Food intake, its quality and calorie measurement. A successful framework will enhance better leaving of the individuals and allows individual to consume the food in a well optimized manner. A real-time framework is developed to monitor eating pattern of the individuals during their food intake. Food recognition and tracking is implemented using machine learning based on the support vector machines (SVM). When the food consumption among the people increases, the problem related to the food also increases. Hence in this paper we introduce a food recognition system in which calories are measured along with the food detection. We create a dataset for both the food images and calories present in that food. Food and calories detected are sent through the mail for the user.
引用
收藏
页码:802 / 806
页数:5
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