The use of temporal information in food image analysis

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...

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Main Authors: Wang, Y., He, Y., Zhu, F., Boushey, Carol, Delp, E.
Format: Conference Paper
Published: 2015
Online Access:http://hdl.handle.net/20.500.11937/51248
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author Wang, Y.
He, Y.
Zhu, F.
Boushey, Carol
Delp, E.
author_facet Wang, Y.
He, Y.
Zhu, F.
Boushey, Carol
Delp, E.
author_sort Wang, Y.
building Curtin Institutional Repository
collection Online Access
description 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.
first_indexed 2025-11-14T09:47:22Z
format Conference Paper
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institution Curtin University Malaysia
institution_category Local University
last_indexed 2025-11-14T09:47:22Z
publishDate 2015
recordtype eprints
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spelling curtin-20.500.11937-512482018-03-29T09:09:36Z The use of temporal information in food image analysis Wang, Y. He, Y. Zhu, F. Boushey, Carol Delp, E. 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. 2015 Conference Paper http://hdl.handle.net/20.500.11937/51248 10.1007/978-3-319-23222-5_39 restricted
spellingShingle Wang, Y.
He, Y.
Zhu, F.
Boushey, Carol
Delp, E.
The use of temporal information in food image analysis
title The use of temporal information in food image analysis
title_full The use of temporal information in food image analysis
title_fullStr The use of temporal information in food image analysis
title_full_unstemmed The use of temporal information in food image analysis
title_short The use of temporal information in food image analysis
title_sort use of temporal information in food image analysis
url http://hdl.handle.net/20.500.11937/51248