Catarina Runa Miranda

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Facial emotions provide an essential source of information commonly used in human communication. For humans, their recognition is automatic and is done exploiting the real-time variations of facial features. However, the replication of this natural process using computer vision systems is still a challenge, since automation and real-time system requirements(More)
The aim of this work is to propose a multifractal analysis method for Multifractal Detrended Fluctuation analysis (MF-DFA) of Blood Oxygen Level Dependent (BOLD) functional Magnetic Resonance Imaging (fMRI). The fMRI signals exhibit a 1/f power spectrum, hence their structure has self-similarity and long memory, being usually successfully analyzed by(More)
Each human face is unique. It has its own shape, topology, and distinguishing features. As such, developing and testing facial tracking systems are challenging tasks. The existing face recognition and tracking algorithms in Computer Vision mainly specify concrete situations according to particular goals and applications, requiring validation methodologies(More)
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