murino
univrit
Monday,
Hours 5:00 PM
- 6:30 PM,
Ca' Vignal 2, Floor 1, room 1.60
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Curriculum Vitae
(pdf, it, 263 KB, 28/04/23)
Modules running in the period selected: 57.
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MyUnivrDi seguito sono elencati gli eventi e gli insegnamenti di Terza Missione collegati al docente:
| Topic | Description | Research area |
|---|---|---|
| Behavior analysis | The goal is to study human inner and outer behavior in order to find possible brain correlates with the (outer) expressive behavior. In the context of behavioral diseases (e.g., autism, schizophrenia, Alzhaimer, Mild Cognitive Impairment, etc.), the main idea is to exploit computer vision and pattern recognition techniques to analyse nonverbal human behavior (face, posture, gesture, etc.) as well as neuroimaging data so to identify possible correlations or characteristic biomarkers. This research not only would support early diagnosis of the pathology but also the monitoring of the effects of the pharmacological treatment. |
Bioinformatics and medical informatics
Machine learning |
| Behavior analysis | The goal is to study human inner and outer behavior in order to find possible brain correlates with the (outer) expressive behavior. In the context of behavioral diseases (e.g., autism, schizophrenia, Alzhaimer, Mild Cognitive Impairment, etc.), the main idea is to exploit computer vision and pattern recognition techniques to analyse nonverbal human behavior (face, posture, gesture, etc.) as well as neuroimaging data so to identify possible correlations or characteristic biomarkers. This research not only would support early diagnosis of the pathology but also the monitoring of the effects of the pharmacological treatment. |
Artificial Intelligence
Machine learning |
| Image processing and computer vision | Basic image processing, e.g. image enhancement, interpolation (digital zooming). Image processing applied to medical images, 2D and 3D segmentation, feature extraction, texture analysis. Optical flow extraction and processing. | IMAGE PROCESSING AND COMPUTER VISION |
| Modellazione statistica di dati multimediali | Modellazione di immagini e video, utilizzando strumenti statistici e probabilistici, quali modelli generativi (misture di Gaussiane, modelli di Markov a stati nascosti), discriminativi (Kernel Machines) ed embedding generativi, in spazi euclidei e non. Tale modellazione porta ad applicazioni come riconoscimento e rivelamento di oggetti, tracking, che si collocano nell'ambito della video sorveglianza, analisi di dati medicali e nell'analisi di segnali sociali o social signal processing. In particolare, le mie specialità attuali sono la re-identificazione e la detection per la sorveglianza, la segmentazione e classificazione per l'analisi di segnali medicali e l'analisi di attività interattive per il social signal processing. |
Bioinformatics and medical informatics
Artificial intelligence |
| Modellazione statistica di dati multimediali | Modellazione di immagini e video, utilizzando strumenti statistici e probabilistici, quali modelli generativi (misture di Gaussiane, modelli di Markov a stati nascosti), discriminativi (Kernel Machines) ed embedding generativi, in spazi euclidei e non. Tale modellazione porta ad applicazioni come riconoscimento e rivelamento di oggetti, tracking, che si collocano nell'ambito della video sorveglianza, analisi di dati medicali e nell'analisi di segnali sociali o social signal processing. In particolare, le mie specialità attuali sono la re-identificazione e la detection per la sorveglianza, la segmentazione e classificazione per l'analisi di segnali medicali e l'analisi di attività interattive per il social signal processing. |
Artificial Intelligence
Artificial intelligence |
| Neuroimaging Data Analysis | This domain regards the analysis of data coming from sensing devices measuring the brain strucural and functional information. The main utilised device is Magnetic Resonance Imaging (MRI) in its various modalities such as diffusion, structural, and functional MRI, as well as other sensors like EEG, fNIRS, MEG. The main goal is to better understanding brain functions by means of an integrated functional and structural analysis of the brain connectivity or of specific brain regions. This investigation is mainly performed with reference to neurological disorders - like autism and schizophrenia - and in comparison with control (healthy) subjects. |
Bioinformatics and medical informatics
Machine learning |
| Neuroimaging Data Analysis | This domain regards the analysis of data coming from sensing devices measuring the brain strucural and functional information. The main utilised device is Magnetic Resonance Imaging (MRI) in its various modalities such as diffusion, structural, and functional MRI, as well as other sensors like EEG, fNIRS, MEG. The main goal is to better understanding brain functions by means of an integrated functional and structural analysis of the brain connectivity or of specific brain regions. This investigation is mainly performed with reference to neurological disorders - like autism and schizophrenia - and in comparison with control (healthy) subjects. |
Artificial Intelligence
Machine learning |
| Sistemi avanzati per il riconoscimento | Due sono gli ambiti principali di ricerca: 1) studio di descrittori di basso livello per addestrare classificatori avanzati; in questo caso, l'idea è di progettare descrittori compatti e informativi per l'object recognition e detection. Particolare enfasi viene data allo studio di descrittori giacenti su spazi non euclidei, come varietà Riemanniane, manipolando nozioni di Information Geometry 2) studio di tecniche di classificazione ibride generative e discriminative; qui l'obiettivo è di sfruttare le caratteristiche vincenti dei modelli generativi (misture di Gaussiane, modelli di Markov a stati nascosti, topic models) e dei modelli discriminativi (Support Vector Machines) combinandole attraverso meccanismi di embedding. In tal maniera, le misure di bontà dei classificatori risultanti superano quelle dei modelli di partenza. |
Bioinformatics and medical informatics
Artificial intelligence |
| Sistemi avanzati per il riconoscimento | Due sono gli ambiti principali di ricerca: 1) studio di descrittori di basso livello per addestrare classificatori avanzati; in questo caso, l'idea è di progettare descrittori compatti e informativi per l'object recognition e detection. Particolare enfasi viene data allo studio di descrittori giacenti su spazi non euclidei, come varietà Riemanniane, manipolando nozioni di Information Geometry 2) studio di tecniche di classificazione ibride generative e discriminative; qui l'obiettivo è di sfruttare le caratteristiche vincenti dei modelli generativi (misture di Gaussiane, modelli di Markov a stati nascosti, topic models) e dei modelli discriminativi (Support Vector Machines) combinandole attraverso meccanismi di embedding. In tal maniera, le misure di bontà dei classificatori risultanti superano quelle dei modelli di partenza. |
Artificial Intelligence
Artificial intelligence |
| Pattern Recognition | The main focus is on the study and development of automatic techniques and models able to extract information from real world data, typically in terms of classes or clusters. Special attention is on probabilistic models - like Hidden Markov Models, Mixtures, Topic Models - and on kernel machines - like Support Vector Machines. In these contexts the interest is in designing novel models/methodologies, like hybrid generative-discriminative methods, generative embeddings and kernels, novel classification or clustering schemes, model selection techniques and others. The focus is on reasoning on representation issues (how to extract features, how to process the original problem space) as well as on unconventional employment of standard techniques (like boosting or SVM for clustering). Another field of interest is the processing of sequential data (using for example Hidden Markov Model). |
Bioinformatics and medical informatics
Machine learning |
| Pattern Recognition | The main focus is on the study and development of automatic techniques and models able to extract information from real world data, typically in terms of classes or clusters. Special attention is on probabilistic models - like Hidden Markov Models, Mixtures, Topic Models - and on kernel machines - like Support Vector Machines. In these contexts the interest is in designing novel models/methodologies, like hybrid generative-discriminative methods, generative embeddings and kernels, novel classification or clustering schemes, model selection techniques and others. The focus is on reasoning on representation issues (how to extract features, how to process the original problem space) as well as on unconventional employment of standard techniques (like boosting or SVM for clustering). Another field of interest is the processing of sequential data (using for example Hidden Markov Model). |
Artificial Intelligence
Machine learning |
| Video Surveillance and Monitoring | This research aims at the analysis of people and the interpretation/recognition of human activities, possibly at the detection and prediction of events in unconstrained scenes, at individual, group and crowd level. In particular, the main target is on the analysis of nonverbal human behaviour, activities, and dialogue classification by considering vocal behavior, face & gazing, gesture & posture, space & environment. More specifically, the focus is on tracking and re-identification, object/person detection and classification, human pose estimation and activity recognition, automatic PTZ camera control, subjective surveillance, mobile sensing, data fusion. |
Bioinformatics and medical informatics
Artificial intelligence |
| Video Surveillance and Monitoring | This research aims at the analysis of people and the interpretation/recognition of human activities, possibly at the detection and prediction of events in unconstrained scenes, at individual, group and crowd level. In particular, the main target is on the analysis of nonverbal human behaviour, activities, and dialogue classification by considering vocal behavior, face & gazing, gesture & posture, space & environment. More specifically, the focus is on tracking and re-identification, object/person detection and classification, human pose estimation and activity recognition, automatic PTZ camera control, subjective surveillance, mobile sensing, data fusion. |
Artificial Intelligence
Artificial intelligence |
| Computer Vision | Investigation of computational tools for the analysis of images and videos, with main goal of extracting useful information. In particular, 2D/3D object classification, 3D reconstruction, person detection and classification, video analysis and understanding, activity recognition, and in biometrics (face recognition and authentication, facial feature extraction, multimodal biometrics, behavioural biometrics) with application in video surveillance and biomedical image analysis. |
Bioinformatics and medical informatics
Artificial intelligence |
| Computer Vision | Investigation of computational tools for the analysis of images and videos, with main goal of extracting useful information. In particular, 2D/3D object classification, 3D reconstruction, person detection and classification, video analysis and understanding, activity recognition, and in biometrics (face recognition and authentication, facial feature extraction, multimodal biometrics, behavioural biometrics) with application in video surveillance and biomedical image analysis. |
Artificial Intelligence
Artificial intelligence |
| Office | Collegial Body |
|---|---|
| member | Computer Science Teaching Committee - Department Computer Science |
| member | Information Engineering Teaching Committee - Department Department of Engineering for Innovation Medicine |
| member | Comitato Scientifico del Master in Comitato Scientifico del Master in Progettazione Multimediale e Video |
| Scientific committee for the Master in Medical Biomedical data and telecontrol Information technology Elaboration | |
| Scientific committee for the Masters in Multimedia and Video Creation | |
| member | Computer Science Department Council - Department Computer Science |
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