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Recognition and Localization of Food in Cooking Videos

Abstract : In this paper, we describe experiments with techniques for locating foods and recognizing food states in cooking videos. We describe production of a new data set that provides annotated images for food types and food states. We compare results with two techniques for detecting food types and food states, and then show that recognizing type and state with separate classifiers improves recognition results. We then use this to provide detection of composite activation maps for food types. The results provide a promising first step towards construction of narratives for cooking actions.
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https://hal.archives-ouvertes.fr/hal-01815512
Contributor : Nachwa Aboubakr <>
Submitted on : Thursday, June 14, 2018 - 3:41:45 PM
Last modification on : Thursday, November 19, 2020 - 1:01:26 PM
Long-term archiving on: : Monday, September 17, 2018 - 12:33:19 PM

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Nachwa Aboubakr, Rémi Ronfard, James L. Crowley. Recognition and Localization of Food in Cooking Videos. Joint Workshop on Multimedia for Cooking and Eating Activities and Multimedia Assisted Dietary Management in conjunction with the 27th International Joint Conference on Artificial Intelligence IJCAI Proceedings, Jul 2018, Stockholm, Sweden. ⟨10.1145/3230519.3230590⟩. ⟨hal-01815512v1⟩

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