Abstract
In this paper nine mobile food recognition systems are described based on their system architecture and their core properties (the core properties and experimental results are shown on the last page). While the mobile hardware increased its power through the years (2009 - 2013) and the food detection algorithms got optimized, still there was no uniform approach to the question of food detection. Also, some system used additional information for better detection, like voice data, OCR and bounding boxes. Three systems included a volume estimation feature. First five systems were implemented on a client-server architecture, while the last three took advantage of the available hardware in later years and proposed a client only based architecture.
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Knez, S., Ĺ ajn, L. (2015). Food Object Recognition Using a Mobile Device: State of the Art. In: Murino, V., Puppo, E., Sona, D., Cristani, M., Sansone, C. (eds) New Trends in Image Analysis and Processing -- ICIAP 2015 Workshops. ICIAP 2015. Lecture Notes in Computer Science(), vol 9281. Springer, Cham. https://doi.org/10.1007/978-3-319-23222-5_45
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DOI: https://doi.org/10.1007/978-3-319-23222-5_45
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