{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/deep-learning-based-food-calorie-estimation","title":"Deep Learning-Based Food Calorie Estimation Method in Dietary Assessment","arxiv_id":"1706.04062","date":"2017-06-10","proceeding":null,"authors":["Yanchao Liang","Jianhua Li"],"abstract":"Obesity treatment requires obese patients to record all food intakes per day.\nComputer vision has been introduced to estimate calories from food images. In\norder to increase accuracy of detection and reduce the error of volume\nestimation in food calorie estimation, we present our calorie estimation method\nin this paper. To estimate calorie of food, a top view and side view is needed.\nFaster R-CNN is used to detect the food and calibration object. GrabCut\nalgorithm is used to get each food's contour. Then the volume is estimated with\nthe food and corresponding object. Finally we estimate each food's calorie. And\nthe experiment results show our estimation method is effective.","url_abs":"http://arxiv.org/abs/1706.04062v4","url_pdf":"http://arxiv.org/pdf/1706.04062v4.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"deep-learning-based-food-calorie-estimation","repo_url":"https://github.com/Liang-yc/CalorieEstimation","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"deep-learning","task_name":"Deep Learning"},{"task_slug":"object","task_name":"Object"}],"methods":[{"method_slug":"convolution","method_name":"Convolution"},{"method_slug":"faster-r-cnn","method_name":"Faster R-CNN"},{"method_slug":"rpn","method_name":"RPN"},{"method_slug":"roipool","method_name":"RoIPool"},{"method_slug":"softmax","method_name":"Softmax"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}