Marco Moltisanti

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The classification of food images is an interesting and challenging problem since the high variability of the image content which makes the task difficult for current state-of-the-art classification methods. The image representation to be employed in the classification engine plays an important role. We believe that texture features have been not properly(More)
In the last two decades multimedia, and in particular imaging devices (camcorders, tablets, mobile phones, etc.) have been dramatically diffused. Moreover the increasing of their computational performances, combined with an higher storage capability, allows them to process large amount of data. In this paper an overview of the current trends of consumer(More)
The growth of popularity of Social Network Services (SNSs) opened new perspectives in many research fields, including the emerging area of Multimedia Forensics. In particular, the huge amount of images uploaded to the social networks can represent a significant source of evidence for investigations, if properly processed. This work aims to exploit the(More)
Automatic food understanding from images is an interesting challenge with applications in different domains. In particular, food intake monitoring is becoming more and more important because of the key role that it plays in health and market economies. In this paper, we address the study of food image processing from the perspective of Computer Vision. As(More)
—Image Forensics has already achieved great results for the source camera identification task on images. Standard approaches for data coming from Social Network Platforms cannot be applied due to different processes involved (e.g., scaling, compression, etc.). Over 1 billion images are shared each day on the Internet and obtaining information about their(More)
Food recognition is an interesting and challenging problem with applications in medical, social and anthropological research areas. The high variability of food images makes the recognition task difficult for current state-of-the-art methods. It has been proved that the exploitation of multiple features to capture complementary aspects of the image contents(More)
Computational Aesthetics applied on digital photography is becoming an interesting issue in different frameworks (e.g., photo album summarization, imaging acquisition devices). Although it is widely believed and can often be experimentally demonstrated that aesthetics is mainly subjective, we aim to find some formal or mathematical explanations of(More)
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