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Person re-identification in a non-overlapping multi-camera scenario is an open and interesting challenge. While the task can hardly be completed by machines, we, as humans, are inherently able to sample those relevant persons’ details that allow us to correctly solve the problem in a fraction of a second. Thus, knowing where a human might fixate to recognize a person is of paramount interest for re-identification...
Food recognition is an emerging computer vision topic. The problem is characterized by the absence of rigid structure of the food and by the large intra-class variations. Existing approaches tackle the problem by designing ad-hoc feature representations based on a priori knowledge of the problem. Differently from these, we propose a committee-based recognition system that chooses the optimal features...
The aim of this paper is to evaluate the effectiveness of a class of data-driven physical models to represent both acoustic and high-speed video data of the voice production process. Voice production analysis through numerical models of the phonation process is nowday a mature research field, and reliable dynamical glottal models of different accuracy and complexity are available. Although they are...
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