Project REWIND

With the rapid proliferation of inexpensive acquisition and storage devices, multimedia objects can be easily created, stored, transmitted, modified and tampered with by anyone. During its lifetime, a digital object might go through several processing stages, including multiple analog-to-digital (A/D) and digital-to-analog (D/A) conversions, coding and decoding, transmission, editing (either aimed at enhancing the quality, creating new content, mixing pre-existing material, or tampering with the content).
The REWIND project (funded within the FP7 ICT FET-Open funding scheme) starts from the fact that each of these processing steps necessarily leaves a characteristic footprint, which can be potentially detected and analyzed to trace back the past history of the available multimedia object in a blind fashion, i.e. without having access to the original content.

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Project Barcotica

Barcotica is an industrial research project involving Monte Carlo Yachts spa, Eidon Kaires srl, AREA Science Park, Università degli Studi di Udine, Consorzio per l’Alta Ricerca Navale RINAVE. The main aim is to design innovative solutions for boats that make navigation easier and more accessible.
Within this project, we worked on the automatic navigation system improving the algorithms for object detection and identification. More precisely, we targeted the problem of the quality of images and videos in the detection.

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Research area: 3D acquisition, transmission and reconstruction

In this field, I worked on the design of enhanced systems able to acquire, denoise, compress and transmit DIBR video signals.
At the moment, his work mainly concerns the design of low complexity strategy for the refinement of the quality of an image or a 3D model. This has been performed for 3D video signals and models acquired via infrared sensors like Time-of-Flight cameras and structured light sensor, like MS Xbox Kinect. Part of this research was devoted to the creation of “intelligent systems” that are able to understand the surrounding reality and drives the choices of an artificial brain. The designed algorithms also concerned standard images that had to be processed by object detection algorithm or used in navigation systems. In this research, a specific attention has been paid to computational complexity and feasibility of these approaches on battery-alimented devices. To this purpose he has designed several cross-layer architectures until defining novel “cognitive source coding schemes”, i.e. reconfigurable systems that, according to the network status, can implement several source coding strategies (predictive, Wyner-Ziv, etc...) by assembling a common set of atomic units. Moreover, we have developed novel 3D video compression techniques that are able to obtain high coding performance thanks to the exploitation of geometry information and advanced transforms.

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