Marcelo de M. Coelho

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—The ability to filter improper content from mul-timedia sources based on visual content has important applications , since text-based filters are clearly insufficient against erroneous and/or malicious associations between text and actual content. In this paper, we investigate a method for detection of nudity in videos based on a bag-of-visual-features(More)
In this paper we compare the use of several features in the task of content filtering for video social networks, a very challenging task, not only because the unwanted content is related to very high-level semantic concepts (e.g., pornography, violence, etc.) but also because videos from social networks are extremely assorted, limiting the use of a priori(More)
Fig. 1. Improvement of image matching by using subspace clustering: the first line shows normal matching where the query (first left image) is matched with the 209 th (last image) returned database image. After our method, at the second line, query image (first left image) is recognized as the 2 nd (third image) returned database image. Abstract—We present(More)
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