Yuri Almeida Lacerda

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Advances in mobile devices, sensors and wireless networks have motivated the development of context-aware applications. Such mobile applications use sensors for monitoring several features such as: location, temperature, velocity, weather, traffic jam, noise, air pollution, and so on. This monitoring enables service provision according to a given context.(More)
The recent popularity of digital cameras has posed a new problem: how to efficiently store and retrieve the very large number of digital photos captured and chaotically stored in multiple locations without any annotation. This paper proposes an infrastructure, called PhotoGeo, which aims at helping users with the people photo annotation, event photo(More)
Knowledge discovery in large online photographic repositories has been an active area of research in recent years. This is due to the great popularization of devices equipped with image capture, such as digital cameras, smartphones and tablets. Moreover, the image files generated by those devices are easily spread out on the Web through social networking(More)
Nowadays the photo-capturing devices are no longer limited to digital cameras but include mobile phones, PDAs and others. This is leading to a new problem: a very large number of digital photos captured and chaotically stored in multiple locations without being annotated. This paper presents a new system, called PhotoGeo, for self-organization of(More)
Digital photography is definitively becoming very popular due to several advantages over the analog one which include easy processing, copying, sharing and cheap storing. Moreover, storage devices for digital photos are getting cheaper and photo-capturing devices are no longer limited to digital cameras but include mobile phones, PDAs and others. As a(More)
Recently, digital photography is definitely becoming very popular. Thus, there is a large increase in the number of captured photos, which demands better methods to manage this data. An approach is to allow the user to annotate some information in those photos, for instance, the people who appear in them. In this paper, two solutions are proposed in order(More)
Several works have exploited the geographic information of photos through spatial clustering algorithms aiming at the automatic discovery of points of interest (POIs). The assumption is that dense regions in terms of geographically nearby photos are good POI surrogates. However, this approach fails when: (i) nearby photos point to different POIs, and (ii)(More)
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