The use of temporal information in food image analysis
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We have developed a dietary assessment system that uses food images captured by a mobile device. Food identification is a crucial component of our system. Achieving a high classification rates is challenging due to the large number of food categories and variability in food appearance. In this paper, we propose to improve food classification by incorporating temporal information. We employ recursive Bayesian estimation to incrementally learn from a person’s eating history. We show an improvement of food classification accuracy by 11% can be achieved.
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