Reconstruction from image correspondences

A single picture provides a largely incomplete representation of the scene one is looking at. Usually it reproduces only a limited spatial portion of the scene according to the standpoint and the viewing angle, besides it contains only instantaneous information. Thus very little can be understood on the geometrical structure of the scene, the position and orientation of the observer with respect to it remaining also hard to guess. When multiple views, taken from different positions in space and time, observe the same scene, then a much deeper knowledge is potentially achievable. Understanding inter-views relations enables construction of a collective representation by fusing the information contained in every single image. Visual reconstruction methods confront with the formidable, and still unanswered, challenge of delivering a comprehensive representation of structure, motion and appearance of a scene from visual information. Multi-view visual reconstruction deals with the inference of relations among multiple views and the exploitation of revealed connections to attain the best possible representation. This thesis investigates novel methods and applications in the field of visual reconstruction from multiple views. Three main threads of research have been pursued: dense geometric reconstruction, camera pose reconstruction, sparse geometric reconstruction of deformable surfaces. Dense geometric reconstruction aims at delivering the appearance of a scene at every single point. The construction of a large panoramic image from a set of traditional pictures has been extensively studied in the context of image mosaicing techniques. An original algorithm for sequential registration suitable for real-time applications has been conceived. The integration of the algorithm into a visual surveillance system has lead to robust and efficient motion detection with Pan-Tilt-Zoom cameras. Moreover, an evaluation methodology for quantitatively assessing and comparing image mosaicing algorithms has been devised and made available to the community. Camera pose reconstruction deals with the recovery of the camera trajectory across an image sequence. A novel mosaic-based pose reconstruction algorithm has been conceived that exploit image-mosaics and traditional pose estimation algorithms to deliver more accurate estimates. An innovative markerless vision-based human-machine interface has also been proposed, so as to allow a user to interact with a gaming applications by moving a hand held consumer grade camera in unstructured environments. Finally, sparse geometric reconstruction refers to the computation of the coarse geometry of an object at few preset points. In this thesis, an innovative shape reconstruction algorithm for deformable objects has been designed. A cooperation with the Solar Impulse project allowed to deploy the algorithm in a very challenging real-world scenario, i.e. the accurate measurements of airplane wings deformations.

Progetto di reti Sensori Wireless e tecniche di Fusione Sensoriale

Ambient Intelligence (AmI) envisions a world where smart, electronic environments are aware and responsive to their context. People moving into these settings engage many computational devices and systems simultaneously even if they are not aware of their presence. AmI stems from the convergence of three key technologies: ubiquitous computing, ubiquitous communication and natural interfaces. The dependence on a large amount of fixed and mobile sensors embedded into the environment makes of Wireless Sensor Networks one of the most relevant enabling technologies for AmI. WSN are complex systems made up of a number of sensor nodes, simple devices that typically embed a low power computational unit (microcontrollers, FPGAs etc.), a wireless communication unit, one or more sensors and a some form of energy supply (either batteries or energy scavenger modules). Low-cost, low-computational power, low energy consumption and small size are characteristics that must be taken into consideration when designing and dealing with WSNs. In order to handle the large amount of data generated by a WSN several multi sensor data fusion techniques have been developed. The aim of multisensor data fusion is to combine data to achieve better accuracy and inferences than could be achieved by the use of a single sensor alone. In this dissertation we present our results in building several AmI applications suitable for a WSN implementation. The work can be divided into two main areas: Multimodal Surveillance and Activity Recognition. Novel techniques to handle data from a network of low-cost, low-power Pyroelectric InfraRed (PIR) sensors are presented. Such techniques allow the detection of the number of people moving in the environment, their direction of movement and their position. We discuss how a mesh of PIR sensors can be integrated with a video surveillance system to increase its performance in people tracking. Furthermore we embed a PIR sensor within the design of a Wireless Video Sensor Node (WVSN) to extend its lifetime. Activity recognition is a fundamental block in natural interfaces. A challenging objective is to design an activity recognition system that is able to exploit a redundant but unreliable WSN. We present our activity in building a novel activity recognition architecture for such a dynamic system. The architecture has a hierarchical structure where simple nodes performs gesture classification and a high level meta classifiers fuses a changing number of classifier outputs. We demonstrate the benefit of such architecture in terms of increased recognition performance, and fault and noise robustness. Furthermore we show how we can extend network lifetime by performing a performance-power trade-off. Smart objects can enhance user experience within smart environments. We present our work in extending the capabilities of the Smart Micrel Cube (SMCube), a smart object used as tangible interface within a tangible computing framework, through the development of a gesture recognition algorithm suitable for this limited computational power device. Finally the development of activity recognition techniques can greatly benefit from the availability of shared dataset. We report our experience in building a dataset for activity recognition. Such dataset is freely available to the scientific community for research purposes and can be used as a testbench for developing, testing and comparing different activity recognition techniques.

Sviluppo e validazione di indicatori di qualità dell’assistenza nell’ambito della salute mentale in Emilia-Romagna

In Italia, il processo di de-istituzionalizzazione e di implementazione di modelli di assistenza per la salute mentale sono caratterizzati da carenza di valutazione. In particolare, non sono state intraprese iniziative per monitorare le attività relative all’assistenza dei pazienti con disturbi psichiatrici. Pertanto, l’obiettivo della tesi è effettuare una valutazione comparativa dei percorsi di cura nell’ambito della salute mentale nei Dipartimenti di Salute Mentale e Dipendenze Patologiche della regione Emilia-Romagna utilizzando indicatori ottenuti dai flussi amministrativi correnti.. I dati necessari alla costruzione degli indicatori sono stati ottenuti attraverso un data linkage dei flussi amministrativi correnti regionali delle schede di dimissione ospedaliera, delle attività territoriali dei Centri di Salute Mentale e delle prescrizioni farmaceutiche, con riferimento all’anno 2010. Gli indicatori sono stati predisposti per tutti i pazienti con diagnosi principale psichiatrica e poi suddivisi per categoria diagnostica in base al ICD9-CM. . Il set di indicatori esaminato comprende i tassi di prevalenza trattata e di incidenza dei disturbi mentali, i tassi di ospedalizzazione, la ri-ospedalizzazione a 7 e 30 giorni dalla dimissione dai reparti psichiatrici, la continuità assistenziale ospedale-territorio, l’adesione ai trattamenti ed il consumo e appropriatezza prescrittiva di farmaci. Sono state rilevate alcune problematiche nella ricostruzione della continuità assistenziale ospedale-territorio ed alcuni limiti degli indicatori relativi alle prescrizioni dei farmaci. Il calcolo degli indicatori basato sui flussi amministrativi correnti si presenta fattibile, pur con i limiti legati alla qualità, completezza ed accuratezza dei dati presenti. L’implementazione di questi indicatori su larga scala (regionale e nazionale) e su base regolare può essere una opportunità per impostare un sistema di sorveglianza, monitoraggio e valutazione dell’assistenza psichiatrica nei DSM.