DocumentCode :
2934451
Title :
Fast food recognition from videos of eating for calorie estimation
Author :
Wu, Wen ; Yang, Jie
Author_Institution :
Language Technol. Inst., Carnegie Mellon Univ., Pittsburgh, PA, USA
fYear :
2009
fDate :
June 28 2009-July 3 2009
Firstpage :
1210
Lastpage :
1213
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.
Keywords :
computer vision; data acquisition; health care; medical computing; video signal processing; calorie estimation; computer food recognition programs; dietary data; eating videos; fast food recognition; obesity etiology; Computer science; Food technology; Humans; Image analysis; Image databases; Image recognition; Technology management; US Department of Agriculture; Videos; Visual databases; calorie estimation; fast food recognition;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Multimedia and Expo, 2009. ICME 2009. IEEE International Conference on
Conference_Location :
New York, NY
ISSN :
1945-7871
Print_ISBN :
978-1-4244-4290-4
Electronic_ISBN :
1945-7871
Type :
conf
DOI :
10.1109/ICME.2009.5202718
Filename :
5202718
Link To Document :
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