Publications

Sensing floors are becoming an emerging solution for many privacy-compliant and large area surveillance systems. Many research and even commercial Technologies have been proposed in the last years. Similarly to distributed camera networks, the problem of calibration is crucial, specially when installed in wide areas. This paper addresses the general problem of automatic calibration and configuration of modular and scalable sensing floors. Working on training data only, the system automatically finds the spatial placement of each sensor module and estimates threshold parameters needed for people detection. Tests on several training sequences captured with a commercial sensing floor are provided to validate the method

This paper presents a novel approach to evaluate game level design strategies, applied to role playing games. Following a set of well defined guidelines, two game levels were designed for Neverwinter Nights 2 to manipulate particular emotions like boredom or flow, and tested by 13 subjects wearing a brain computer interface helmet. A set of features was extracted from the affective data logs and used to classify different parts of the gaming sessions, to verify the correspondence of the original level aims and the effective results on people emotions. The very interesting correlations observed, suggest that the technique is extensible to other similar evaluation tasks.

JAK/STAT3 signaling pathway is often deregulated in hematopoietic disorders including peripheral T-cell lymphoma. We describe two novel mechanisms leading to the constitutive activation of STAT3 in ALK- ALCL. Oncogenic JAK1 or STAT3 mutations are associated to hyperactive pSTAT3 that regulated canonical STAT3 and ATF3 genes. Moreover, synergizing JAK1 and STAT3 mutants sustain the neoplastic growth, which can be efficiently controlled in vitro and in an ALCL patient derived tumorgraft model by JAK1/2 inhibitors. We have discovered that novel chimera, displaying concomitant transcriptional and kinase activities, are power oncogenes capable to sustain via STAT3 the ALCL phenotype and can be uniquely neutralized by a novel ROS1 inhibitor. The pharmacological inhibition of JAK/STAT3 represents a novel strategy for the treatment of molecular stratified ALCL.

Following the recent Internet of Everything (IoE) trend, several general-purpose devices have been proposed to acquire as much information as possible from the environment and from people interacting with it. Among the others, sensing floors are recently attracting the interest of the research community. In this paper, we propose a new model to store and process floor data. The model does not assume a regular grid distribution of the sensing elements and is based on the ground reaction force (GRF) concept, widely used in biomechanics. It allows the correct detection and tracking of people, outperforming the common background subtraction schema adopted in the past. Several tests on a real sensing floor prototype are reported and discussed

Tracking objects moving around a person is one of the key steps in human visual augmentation: we could estimate their locations when they are out of our field of view, know their position, distance or velocity just to name a few possibilities. This is no easy task: in this paper, we show how current state-of-the-art visual tracking algorithms fail if challenged with a first-person sequence recorded from a wearable camera attached to a moving user. We propose an evaluation that highlights these algorithms' limitations and, accordingly, develop a novel approach based on visual odometry and 3D localization that overcomes many issues typical of egocentric vision. We implement our algorithm on a wearable board and evaluate its robustness, showing in our preliminary experiments an increase in tracking performance of nearly 20\% if compared to currently state-of-the-art techniques.

In this paper we propose a novel approach for egocentric video personalization in a cultural experience scenario, based on shots automatic labelling according to different semantic dimensions, such as web leveraged knowledge of the surrounded cultural Points Of Interest, information about stops and moves, both relying on geolocalization, and camera’s wearer behaviour. Moreover we present a video personalization web system based on shots multi-dimensional semantic classification, that is designed to aid the visitor to browse and to retrieve relevant information to obtain a customized video. Experimental results show that the proposed techniques for video analysis achieve good performances in unconstrained scenario and user evaluation tests confirm that our solution is useful and effective.

In this paper, we propose a new method to obtain customized video summarization according to specific user preferences. Our approach is tailored on Cultural Heritage scenario and is designed on identifying candidate shots, selecting from the original streams only the scenes with behavior patterns related to the presence of relevant experiences, and further filtering them in order to obtain a summary matching the requested user's preferences. Our preliminary results show that the proposed approach is able to leverage user's preferences in order to obtain a customized summary, so that different users may extract from the same stream different summaries.