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dc.contributor.authorHe, Y.
dc.contributor.authorXu, C.
dc.contributor.authorKhanna, N.
dc.contributor.authorBoushey, Carol
dc.contributor.authorDelp, E.
dc.date.accessioned2017-03-15T22:17:31Z
dc.date.available2017-03-15T22:17:31Z
dc.date.created2017-02-26T19:31:37Z
dc.date.issued2013
dc.identifier.citationHe, Y. and Xu, C. and Khanna, N. and Boushey, C. and Delp, E. 2013. Food image analysis: Segmentation, identification and weight estimation, in Proceedings of International Conference on Multimedia and Expo (ICME), Jul 15-19 2013. San Jose, CA, USA: IEEE.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/50154
dc.identifier.doi10.1109/ICME.2013.6607548
dc.description.abstract

We are developing a dietary assessment system that records daily food intake through the use of food images taken at a meal. The food images are then analyzed to extract the nutrient content in the food. In this paper, we describe the image analysis tools to determine the regions where a particular food is located (image segmentation), identify the food type (feature classification) and estimate the weight of the food item (weight estimation). An image segmentation and classification system is proposed to improve the food segmentation and identification accuracy. We then estimate the weight of food to extract the nutrient content from a single image using a shape template for foods with regular shapes and area-based weight estimation for foods with irregular shapes.

dc.titleFood image analysis: Segmentation, identification and weight estimation
dc.typeConference Paper
dcterms.source.titleProceedings - IEEE International Conference on Multimedia and Expo
dcterms.source.seriesProceedings - IEEE International Conference on Multimedia and Expo
dcterms.source.isbn9781479900152
curtin.departmentSchool of Public Health
curtin.accessStatusFulltext not available


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