Name
Abstract | ||
|---|---|---|
Accurate and passive acquisition of dietary data from patients is essential for a better understanding of the etiology of obesity and development of effective weight management programs. Self-reporting is currently the main method for such data acquisition. However, studies have shown that data obtained by self-reporting seriously underestimate food intake and thus do not accurately reflect the real habitual behavior of individuals. Computer food recognition programs have not yet been developed. In this paper, we present a study for recognizing foods from videos of eating, which are directly recorded in restaurants by a web camera. From recognition results, our method then estimates food calories of intake. We have evaluated our method on a database of 101 foods from 9 food restaurants in USA and obtained promising results. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1109/ICME.2009.5202718 | ICME |
Keywords | Field | DocType |
underestimate food intake,health care,video signal processing,calorie estimation,passive acquisition,better understanding,dietary data,obesity etiology,eating videos,recognition result,main method,data acquisition,computer food recognition programs,fast food recognition,computer food recognition program,computer vision,medical computing,food restaurant,food calory,weight management,data mining,indexing terms,databases,estimation | Health care,Computer vision,Food recognition,Computer science,Data acquisition,Weight management,Obesity,Artificial intelligence,Calorie | Conference |
ISSN | ISBN | Citations |
1945-7871 E-ISBN : 978-1-4244-1291-1 | 978-1-4244-1291-1 | 27 |
PageRank | References | Authors |
2.38 | 3 | 2 |