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Deep Learning-Based Food Calorie Estimation Method in Dietary Assessment

2017-06-10 · Yanchao Liang, Jianhua Li

Obesity treatment requires obese patients to record all food intakes per day. Computer vision has been introduced to estimate calories from food images. In order to increase accuracy of detection and reduce the error of volume estimation in food calorie estimation, we present our calorie estimation method in this paper. To estimate calorie of food, a top view and side view is needed. Faster R-CNN is used to detect the food and calibration object. GrabCut algorithm is used to get each food's contour. Then the volume is estimated with the food and corresponding object. Finally we estimate each food's calorie. And the experiment results show our estimation method is effective.

📄 PDF Abstract BibTeX arXiv:1706.04062

Code (1)

Liang-yc/CalorieEstimation

Tasks

Deep LearningObject

Methods 이 논문이 사용한 방법론

RPN A Region Proposal Network, or RPN, is a fully convolutional network that simultaneously predicts object bounds and objectness scores at each position. The RPN is trained…
Softmax The Softmax output function transforms a previous layer's output into a vector of probabilities. It is commonly used for multiclass classification. Given an input vector $x$…
RoIPool 설명 없음
Faster R-CNN Faster R-CNN is an object detection model that improves on Fast R-CNN by utilising a region proposal network…
Convolution A convolution is a type of matrix operation, consisting of a kernel, a small matrix of weights, that slides over input data performing element-wise multiplication with the…

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