Our lab conducts innovative research across multimedia and security. Below, you will find a list of our most recent publications.
Recent publications
2024
Ferrarotti, Anna; Baldoni, Sara; Carli, Marco; Battisti, Federica
On the identification of the leading sensory cue in mulsemedia VR applications Conference
2024 16th International Conference on Quality of Multimedia Experience (QoMEX), IEEE, 2024.
@conference{Ferrarotti_QOMEX_2024,
title = {On the identification of the leading sensory cue in mulsemedia VR applications},
author = {Anna Ferrarotti and Sara Baldoni and Marco Carli and Federica Battisti},
doi = {10.1109/QoMEX61742.2024.10598293},
year = {2024},
date = {2024-06-18},
urldate = {2024-06-18},
booktitle = {2024 16th International Conference on Quality of Multimedia Experience (QoMEX)},
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Ferrarotti, Anna; Baldoni, Sara; Carli, Marco; Battisti, Federica
Interaction goes virtual: towards collaborative XR Conference
Proceedings of the 2024 ACM International Conference on Interactive Media Experiences, ACM, 2024.
@conference{Ferrarotti_IMX_2024,
title = {Interaction goes virtual: towards collaborative XR},
author = {Anna Ferrarotti and Sara Baldoni and Marco Carli and Federica Battisti},
doi = {10.1145/3639701.3661089},
year = {2024},
date = {2024-06-07},
booktitle = {Proceedings of the 2024 ACM International Conference on Interactive Media Experiences},
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Sosa, Angel Luis Zuriarrain; Ioannucci, Valeria; Pratesi, Marco; Alesii, Roberto; Albanese, Carlo; Valentini, Francesco; Cinque, Elena; Martinelli, Alessio; Brizzi, Michele
OBU for Accurate Navigation through Sensor Fusion in the Framework of the EMERGE Project Journal Article
In: Applied Sciences, vol. 14, no. 11, 2024, ISSN: 2076-3417.
@article{app14114401,
title = {OBU for Accurate Navigation through Sensor Fusion in the Framework of the EMERGE Project},
author = {Angel Luis Zuriarrain Sosa and Valeria Ioannucci and Marco Pratesi and Roberto Alesii and Carlo Albanese and Francesco Valentini and Elena Cinque and Alessio Martinelli and Michele Brizzi},
url = {https://www.mdpi.com/2076-3417/14/11/4401},
doi = {10.3390/app14114401},
issn = {2076-3417},
year = {2024},
date = {2024-05-22},
journal = {Applied Sciences},
volume = {14},
number = {11},
abstract = {With the development of advanced driver assistance systems (ADAS) and autonomous vehicles (AV), recent years have seen an increasing evolution of onboard sensors and communication interfaces capable of interacting with available infrastructures, including satellite constellations, road structures, modern and heterogeneous network systems (e.g., 5G and beyond) and even adjacent vehicles. Consequently, it is essential to develop architectures that cover data fusion (multi–sensor approach), communication, power management, and system monitoring to ensure accurate and reliable perception in several navigation scenarios. Motivated by the EMERGE project, this paper describes the definition and implementation of an On Board Unit (OBU) dedicated to the navigation process. The OBU is equipped with the Xsens MTi–630 AHRS inertial sensor, a multi–constellation/multi–frequency Global Navigation Satellite System (GNSS) receiver with the u–blox ZED–F9P module and communication interfaces that afford access to the PointPerfect augmentation service. Experimental results show that GNSS, with corrections provided by augmentation, affords centimetre accuracy, with a Time To First Fix (TTFF) of about 30 s. During the on–road tests, we also collect: the output of fusion with inertial sensor data, monitoring information that assess correct operation of the module, and the OBU power consumption, that remains under 5 W even in high–power operating mode.},
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With the development of advanced driver assistance systems (ADAS) and autonomous vehicles (AV), recent years have seen an increasing evolution of onboard sensors and communication interfaces capable of interacting with available infrastructures, including satellite constellations, road structures, modern and heterogeneous network systems (e.g., 5G and beyond) and even adjacent vehicles. Consequently, it is essential to develop architectures that cover data fusion (multi–sensor approach), communication, power management, and system monitoring to ensure accurate and reliable perception in several navigation scenarios. Motivated by the EMERGE project, this paper describes the definition and implementation of an On Board Unit (OBU) dedicated to the navigation process. The OBU is equipped with the Xsens MTi–630 AHRS inertial sensor, a multi–constellation/multi–frequency Global Navigation Satellite System (GNSS) receiver with the u–blox ZED–F9P module and communication interfaces that afford access to the PointPerfect augmentation service. Experimental results show that GNSS, with corrections provided by augmentation, affords centimetre accuracy, with a Time To First Fix (TTFF) of about 30 s. During the on–road tests, we also collect: the output of fusion with inertial sensor data, monitoring information that assess correct operation of the module, and the OBU power consumption, that remains under 5 W even in high–power operating mode.
Brizzi, Michele; Neri, Alessandro
Collaborative RTK Integrity Monitoring Proceedings Article
In: Proceedings of the ION 2024 Pacific PNT Meeting, pp. 106 – 115, The Institute of Navigation ION, 2024, ISBN: 978-0-936406-38-1.
@inproceedings{Brizzi_CoRTKIM_PNT_2024,
title = {Collaborative RTK Integrity Monitoring},
author = {Michele Brizzi and Alessandro Neri},
url = {https://www.ion.org/publications/abstract.cfm?articleID=19626},
doi = {10.33012/2024.19626},
isbn = {978-0-936406-38-1},
year = {2024},
date = {2024-05-09},
urldate = {2024-04-17},
booktitle = {Proceedings of the ION 2024 Pacific PNT Meeting},
pages = {106 - 115},
publisher = {ION},
organization = {The Institute of Navigation},
abstract = {This paper explores the use of Global Navigation Satellite System (GNSS) integrity monitoring techniques into Collaborative RTK systems. Collaborative RTK (C-RTK) leverages the data from multiple GNSS receivers to improve the accuracy and robustness of positioning solutions. By enhancing this collaborative approach with integrity monitoring, we aim to mitigate the impact of errors and anomalies in the GNSS signals, thus enhancing the reliability and safety of applications that depend on high-precision positioning in urban scenarios.},
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This paper explores the use of Global Navigation Satellite System (GNSS) integrity monitoring techniques into Collaborative RTK systems. Collaborative RTK (C-RTK) leverages the data from multiple GNSS receivers to improve the accuracy and robustness of positioning solutions. By enhancing this collaborative approach with integrity monitoring, we aim to mitigate the impact of errors and anomalies in the GNSS signals, thus enhancing the reliability and safety of applications that depend on high-precision positioning in urban scenarios.
Neri, Alessandro; Pascucci, Federica; Brizzi, Michele; Rispoli, Francesco; Ruggeri, Agostino; Cervicato, Cosimo
Use of a GNSS Digital Beamforming Platform for an Assisted Berthing System Proceedings Article
In: Proceedings of the ION 2024 Pacific PNT Meeting, pp. 417 – 429, The Institute of Navigation ION, 2024, ISBN: 978-0-936406-38-1.
@inproceedings{Neri_DBP_PNT_2024,
title = {Use of a GNSS Digital Beamforming Platform for an Assisted Berthing System},
author = {Alessandro Neri and Federica Pascucci and Michele Brizzi and Francesco Rispoli and Agostino Ruggeri and Cosimo Cervicato},
url = {https://www.ion.org/publications/abstract.cfm?articleID=19655},
doi = {10.33012/2024.19655},
isbn = {978-0-936406-38-1},
year = {2024},
date = {2024-05-09},
urldate = {2024-04-18},
booktitle = {Proceedings of the ION 2024 Pacific PNT Meeting},
pages = {417 - 429},
publisher = {ION},
organization = {The Institute of Navigation},
abstract = {The COVID pandemic in 2020 caused an unpredictable disruption to maritime transportation, affecting the smooth operating of the global supply chains. To make this transport sector more resilient a key enabling factor is the introduction of novel smart systems both on port and ship side. This contribution addresses this topic. Specifically, it introduces a GNSS Digital Beamforming Platform (DBP) for an Assisted Berthing System that exploits satellite signals to support officers during docking and undocking manoeuvre. In addition to Position, Velocity and Timing (PVT), the DBP provides a direct estimate of the ship attitude. In fact, in addition to PVT, attitude plays an important role in innovative digital systems for navigation in port waters and for the assisted berthing operations of large cargo RORO Ships. In addition to PVT and Attitude estimation, the proposed DBF offers high resilience against jammers and miconing and spoofing attacks. In this paper we focus our attention on the use of a four array elements, fully coherent DBP for estimation of heading, pitch, and roll and on the evaluation of the achievable performance. Knowledge of the array geometry is fully exploited by means of a constrained least square estimation procedure. Integrity evaluation in terms of protection levels with reference to the estimated distance to the quay side. DBP Performance assessed by means of tests performed with a DBP Proof of Concept and by means of simulations is reported.},
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The COVID pandemic in 2020 caused an unpredictable disruption to maritime transportation, affecting the smooth operating of the global supply chains. To make this transport sector more resilient a key enabling factor is the introduction of novel smart systems both on port and ship side. This contribution addresses this topic. Specifically, it introduces a GNSS Digital Beamforming Platform (DBP) for an Assisted Berthing System that exploits satellite signals to support officers during docking and undocking manoeuvre. In addition to Position, Velocity and Timing (PVT), the DBP provides a direct estimate of the ship attitude. In fact, in addition to PVT, attitude plays an important role in innovative digital systems for navigation in port waters and for the assisted berthing operations of large cargo RORO Ships. In addition to PVT and Attitude estimation, the proposed DBF offers high resilience against jammers and miconing and spoofing attacks. In this paper we focus our attention on the use of a four array elements, fully coherent DBP for estimation of heading, pitch, and roll and on the evaluation of the achievable performance. Knowledge of the array geometry is fully exploited by means of a constrained least square estimation procedure. Integrity evaluation in terms of protection levels with reference to the estimated distance to the quay side. DBP Performance assessed by means of tests performed with a DBP Proof of Concept and by means of simulations is reported.
Brizzi, Michele; Neri, Alessandro
A Virtual Track Velocity Constraint for Integrity Enhancement in Automated Driving Systems Proceedings Article
In: Proceedings of the ION 2024 Pacific PNT Meeting, pp. 444 – 454, The Institute of Navigation ION, 2024, ISBN: 978-0-936406-38-1.
@inproceedings{Brizzi_VVT_PNT_2024,
title = {A Virtual Track Velocity Constraint for Integrity Enhancement in Automated Driving Systems},
author = {Michele Brizzi and Alessandro Neri},
url = {https://www.ion.org/publications/abstract.cfm?articleID=19657},
doi = {10.33012/2024.19657},
isbn = {978-0-936406-38-1},
year = {2024},
date = {2024-05-09},
urldate = {2024-04-18},
booktitle = {Proceedings of the ION 2024 Pacific PNT Meeting},
pages = {444 - 454},
publisher = {ION},
organization = {The Institute of Navigation},
abstract = {The integrity of the positioning information provided to Intelligent Transport Systems and Automated Driving Systems is crucial, as significant solution errors could escalate the risk of accidents. In fact, meeting Automotive Safety Integrity Level-D (ASIL-D) specifications demands decimeter-level accuracy and stringent Tolerable Hazard Rate criteria. However, the integrity of the velocity solution, often overlooked, must also be considered when Advances Driving Assistance Systems and other automated functions rely on Global Navigation Satellite Systems (GNSSs). Building on prior research, this work proposes to enhance the reliability of GNSS-derived velocity estimates thanks to the application of virtual track constraints. These constraints, originally applied in the railway domain, are adapted for automotive scenarios. The proposed system thus integrates GNSS with on-board sensors to align velocity estimates with the expected trajectory provided by a Digital Map of the road. Based on the track-constrained solution, we perform integrity monitoring by implementing the Solution Separation method in the parity space. The study demonstrates a reduction in the horizontal protection levels, emphasizing the effectiveness of virtual track constraints in mitigating errors on the estimated velocity.},
keywords = {},
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The integrity of the positioning information provided to Intelligent Transport Systems and Automated Driving Systems is crucial, as significant solution errors could escalate the risk of accidents. In fact, meeting Automotive Safety Integrity Level-D (ASIL-D) specifications demands decimeter-level accuracy and stringent Tolerable Hazard Rate criteria. However, the integrity of the velocity solution, often overlooked, must also be considered when Advances Driving Assistance Systems and other automated functions rely on Global Navigation Satellite Systems (GNSSs). Building on prior research, this work proposes to enhance the reliability of GNSS-derived velocity estimates thanks to the application of virtual track constraints. These constraints, originally applied in the railway domain, are adapted for automotive scenarios. The proposed system thus integrates GNSS with on-board sensors to align velocity estimates with the expected trajectory provided by a Digital Map of the road. Based on the track-constrained solution, we perform integrity monitoring by implementing the Solution Separation method in the parity space. The study demonstrates a reduction in the horizontal protection levels, emphasizing the effectiveness of virtual track constraints in mitigating errors on the estimated velocity.
Neri, Alessandro; Brizzi, Michele; Vennarini, Alessia; Rispoli, Francesco
On the Integrity of GNSS-IMU Train Positioning Exploiting the Track Constraint Proceedings Article
In: Proceedings of the ION 2024 Pacific PNT Meeting, pp. 463 – 476, The Institute of Navigation ION, 2024, ISBN: 978-0-936406-38-1.
@inproceedings{Neri_IMU_PNT_2024,
title = {On the Integrity of GNSS-IMU Train Positioning Exploiting the Track Constraint},
author = {Alessandro Neri and Michele Brizzi and Alessia Vennarini and Francesco Rispoli},
url = {https://www.ion.org/publications/abstract.cfm?articleID=19659},
doi = {10.33012/2024.19659},
isbn = {978-0-936406-38-1},
year = {2024},
date = {2024-05-09},
urldate = {2024-04-18},
booktitle = {Proceedings of the ION 2024 Pacific PNT Meeting},
pages = {463 - 476},
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Ferrarotti, Anna
QoE Assessment for cultural heritage fruition through immersive media Journal Article
In: Science Talks, 2024.
@article{Ferrarotti_ST_2024,
title = {QoE Assessment for cultural heritage fruition through immersive media},
author = {Anna Ferrarotti},
doi = {10.1016/j.sctalk.2024.100343},
year = {2024},
date = {2024-03-31},
journal = {Science Talks},
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Neri, Michael; Archontis, P.; Krause, D.; Carli, Marco; Virtanen, T.
Speaker Distance Estimation in Enclosures from Single-Channel Audio Journal Article
In: IEEE/ACM Transactions on Audio, Speech, and Language Processing, 2024.
@article{Neri_TASLP_2024,
title = {Speaker Distance Estimation in Enclosures from Single-Channel Audio},
author = {Michael Neri and P. Archontis and D. Krause and Marco Carli and T. Virtanen},
doi = {10.1109/TASLP.2024.3382504},
year = {2024},
date = {2024-01-01},
urldate = {2024-01-01},
journal = {IEEE/ACM Transactions on Audio, Speech, and Language Processing},
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Yan, Penggao; Xia, Xiao; Brizzi, Michele; Wen, Weisong; Hsu, Li-Ta
Subspace-based Adaptive GMM Error Modeling for Fault-Aware Pseudorange-based Positioning in Urban Canyons Journal Article
In: IEEE Transactions on Intelligent Vehicles, pp. 1-16, 2024.
@article{10648803,
title = {Subspace-based Adaptive GMM Error Modeling for Fault-Aware Pseudorange-based Positioning in Urban Canyons},
author = {Penggao Yan and Xiao Xia and Michele Brizzi and Weisong Wen and Li-Ta Hsu},
doi = {10.1109/TIV.2024.3450198},
year = {2024},
date = {2024-01-01},
journal = {IEEE Transactions on Intelligent Vehicles},
pages = {1-16},
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Ferrarotti, Anna; Baldoni, Sara; Carli, Marco; Battisti, Federica
Stress Assessment for Augmented Reality Applications Based on Head Movement Features Journal Article
In: IEEE Transactions on Visualization and Computer Graphics, vol. 30, no. 10, pp. 6970-6983, 2024.
@article{Ferrarotti_TVCG_2024,
title = {Stress Assessment for Augmented Reality Applications Based on Head Movement Features},
author = {Anna Ferrarotti and Sara Baldoni and Marco Carli and Federica Battisti},
doi = {10.1109/TVCG.2024.3385637},
year = {2024},
date = {2024-01-01},
urldate = {2024-01-01},
journal = {IEEE Transactions on Visualization and Computer Graphics},
volume = {30},
number = {10},
pages = {6970-6983},
abstract = {Augmented reality is one of the enabling technologies of the upcoming future. Its usage in working and learning scenarios may lead to a better quality of work and training by helping the operators during the most crucial stages of processes. Therefore, the automatic detection of stress during augmented reality experiences can be a valuable support to prevent consequences on people's health and foster the spreading of this technology. In this work, we present the design of a non-invasive stress assessment approach. The proposed system is based on the analysis of the head movements of people wearing a Head Mounted Display while performing stress-inducing tasks. First, we designed a subjective experiment consisting of two stress-related tests for data acquisition. Then, a statistical analysis of head movements has been performed to determine which features are representative of the presence of stress. Finally, a stress classifier based on a combination of Support Vector Machines has been designed and trained. The proposed approach achieved promising performances thus paving the way for further studies in this research direction.},
keywords = {},
pubstate = {published},
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Augmented reality is one of the enabling technologies of the upcoming future. Its usage in working and learning scenarios may lead to a better quality of work and training by helping the operators during the most crucial stages of processes. Therefore, the automatic detection of stress during augmented reality experiences can be a valuable support to prevent consequences on people's health and foster the spreading of this technology. In this work, we present the design of a non-invasive stress assessment approach. The proposed system is based on the analysis of the head movements of people wearing a Head Mounted Display while performing stress-inducing tasks. First, we designed a subjective experiment consisting of two stress-related tests for data acquisition. Then, a statistical analysis of head movements has been performed to determine which features are representative of the presence of stress. Finally, a stress classifier based on a combination of Support Vector Machines has been designed and trained. The proposed approach achieved promising performances thus paving the way for further studies in this research direction.