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This paper describes the participation of our team MIAR ICT in the ImageCLEF 2013 Robot Vision Challenge. The task of the Challenge asked participants to classify imaged indoor scenes and recognize the predefined objects appeared in the imaged scene. Our approach is based on the recently proposed Kernel Descriptors framework, which is an effective(More)
Food-related photos have become increasingly popular, due to social networks, food recommendation and dietary assessment systems. Reliable annotation is essential in those systems, but unconstrained automatic food recognition is still not accurate enough. Most works focus on exploiting only the visual content while ignoring the context. To address this(More)
The effects of different steps in honey production on chloramphenicol (CAP) levels and CAP removal from honey using macroporous adsorption resins (MARs) were investigated in this study. CAP residues in honey were quantified by enzyme-linked immunosorbent assay after each processing step including preheating, filtration, vacuum concentration and(More)
A large amount of food photos are taken in restaurants for diverse reasons. This dish recognition problem is very challenging, due to different cuisines, cooking styles and the intrinsic difficulty of modeling food from its visual appearance. Contextual knowledge is crucial to improve recognition in such scenario. In particular, geocontext has been widely(More)
Food-related photos have become increasingly very popular, due to social networks, food recommendation and dietary assessment systems. Reliable annotation is essential in those systems, but user-contributed tags are often non-informative and inconsistent, and unconstrained automatic food recognition still has relatively low accuracy. Most works focus on(More)
Food photos are widely used in food logs for diet monitoring and in social networks to share social and gastronomic experiences. A large number of these images are taken in restaurants. Dish recognition in general is very challenging, due to different cuisines, cooking styles and the intrinsic difficulty of modeling food from its visual appearance. However(More)
The phenomenal growth of the usage of mobile devices (e.g., mobile phones and tablet PCs) opens up a new service, namely mobile visual recognition, which has been widely used in many areas, such as mobile shopping and augmented reality. The rich contextual information (e.g., location, time and direction information), easily acquired by the mobile devices,(More)
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