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The accurate performance achieved by current bio-metric recognition systems based on automated fingerprints analysis has induced criminals to evade system identification by altering their fingerprints on purpose. In this paper, we propose a novel approach for detecting altered fingerprints. Our method is based on the combination of multiple complementary features, such as minutiae density maps and...
Visual object tracking in video can be formulated as a time varying appearance-based binary classification problem. Tracking algorithms need to adapt to changes in both foreground object appearance as well as varying scene backgrounds. Fusing information from multimodal features (views or representations) typically enhances classification performance without increasing classifier complexity when image...
We investigate the application of structured output learning (SOL) in automatic annotation of court games. We formulate the problem of event classification in court games as one of learning a mapping from features to structured labels, and employ structured SVM to achieve a max-margin solution. We compare closely the more popular generative approach based on the hidden Markov model (HMM) with our...
Graphical User Interface (GUI) object classification is essential for image-based software automation tools. The challenges posed by GUI object classification are significantly different from those in natural image classification. In this paper we present a novel image descriptor developed specifically for GUI objects; it is robust to various changes in the appearance of GUI objects, such as various...
The understanding of neurodegenerative diseases undoubtedly passes through the study of human brain white matter fiber tracts. To date, diffusion magnetic resonance imaging (dMRI) is the unique technique to obtain information about the neural architecture of the human brain, thus permitting the study of white matter connections and their integrity. However, a remaining challenge of the dMRI community...
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