Our lab conducts innovative research across multimedia and security. Below, you will find a list of our most recent publications.
Recent publications
2026
Fabrizio, Alessia; Rocchi, Erica; Carnevale, Arianna; Ferrarotti, Anna; Papalia, Rocco; Schena, Emiliano; Longo, Umile Giuseppe; Carli, Marco
Performance Evaluation of Meta Quest 3 and Meta Quest Pro in Static and Dynamic Conditions for Shoulder Rehabilitation in Virtual Reality Journal Article
In: IEEE Access, 2026.
@article{Fabrizio_A_2026,
title = {Performance Evaluation of Meta Quest 3 and Meta Quest Pro in Static and Dynamic Conditions for Shoulder Rehabilitation in Virtual Reality},
author = {Alessia Fabrizio and Erica Rocchi and Arianna Carnevale and Anna Ferrarotti and Rocco Papalia and Emiliano Schena and Umile Giuseppe Longo and Marco Carli
},
doi = {10.1109/ACCESS.2026.3679266},
year = {2026},
date = {2026-03-30},
journal = {IEEE Access},
abstract = {Virtual Reality is gaining increasing relevance as a system to monitor joint kinematics during rehabilitation and as a tool to improve patient adherence to rehabilitation protocols. This study aims to evaluate the performance of Meta Quest 3 and Meta Quest Pro by comparing their tracking accuracy against the Qualisys™ stereophotogrammetric reference system in static and dynamic conditions. In static conditions, translational and rotational accuracy were assessed using two custom-made setups: one assessing displacements along three axes (from 0 to 505 mm) and another covering rotations from 0° to 180°. Dynamic performance was evaluated through three clinically relevant upper-limb movements (flexion, external rotation, and abduction) executed by NAO humanoid robot at three different durations (S1 = 1s, S2 = 2s, S4 = 4s) to simulate varying patient conditions. Results showed a maximum translational mean absolute error of 4.7 ± 2.8 mm at 505 mm along the X-axis and a maximum rotational error of 2.8 ± 1.2° at 90° around the Y-axis for Meta Quest 3. In dynamic conditions, the highest mean absolute percentage error was 17.0 ± 2.9% for Meta Quest 3 during abduction at S4. Overall, the Meta Quest 3 and Meta Quest Pro, featuring inside-out tracking technology, demonstrate promising accuracy, supporting their potential use as reliable tools for Virtual Reality-based motor rehabilitation.},
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Virtual Reality is gaining increasing relevance as a system to monitor joint kinematics during rehabilitation and as a tool to improve patient adherence to rehabilitation protocols. This study aims to evaluate the performance of Meta Quest 3 and Meta Quest Pro by comparing their tracking accuracy against the Qualisys™ stereophotogrammetric reference system in static and dynamic conditions. In static conditions, translational and rotational accuracy were assessed using two custom-made setups: one assessing displacements along three axes (from 0 to 505 mm) and another covering rotations from 0° to 180°. Dynamic performance was evaluated through three clinically relevant upper-limb movements (flexion, external rotation, and abduction) executed by NAO humanoid robot at three different durations (S1 = 1s, S2 = 2s, S4 = 4s) to simulate varying patient conditions. Results showed a maximum translational mean absolute error of 4.7 ± 2.8 mm at 505 mm along the X-axis and a maximum rotational error of 2.8 ± 1.2° at 90° around the Y-axis for Meta Quest 3. In dynamic conditions, the highest mean absolute percentage error was 17.0 ± 2.9% for Meta Quest 3 during abduction at S4. Overall, the Meta Quest 3 and Meta Quest Pro, featuring inside-out tracking technology, demonstrate promising accuracy, supporting their potential use as reliable tools for Virtual Reality-based motor rehabilitation.
Ferrarotti, Anna; Rodríguez, Isabel; Usón, Javier; Baldoni, Sara; Barbero, David; Berjón, Daniel; Morán, Francisco; García, Narciso; Battisti, Federica; Gutiérrez, Jesús; Carli, Marco; Cabrera, Julián
Quality assessment of 3D reconstructed meshes: Bridging objective metrics, subjective perception, and behavioral cues Journal Article
In: Signal Processing: Image Communication, vol. 143, 2026.
@article{Ferrarotti_SPIC_2026,
title = {Quality assessment of 3D reconstructed meshes: Bridging objective metrics, subjective perception, and behavioral cues},
author = {Anna Ferrarotti and Isabel Rodríguez and Javier Usón and Sara Baldoni and David Barbero and Daniel Berjón and Francisco Morán and Narciso García and Federica Battisti and Jesús Gutiérrez and Marco Carli and Julián Cabrera},
doi = {https://doi.org/10.1016/j.image.2026.117514},
year = {2026},
date = {2026-01-04},
journal = {Signal Processing: Image Communication},
volume = {143},
abstract = {Assessing the quality of 3D reconstructed models remains a key challenge in multimedia applications, especially in the context of cultural heritage, where visual fidelity and perceptual realism are equally crucial. This study investigates how reconstruction parameters, as well as existing objective quality metrics, align with human perception. In addition, we analyze how perceived quality and user interaction are related. A dataset of 3D models was generated by varying the number of input images, mesh complexity, and texture resolution. Results from a subjective study show that texture resolution significantly affects perceived quality, whereas variations in number of images and mesh complexity have a limited impact. Furthermore, interaction behavior was found to vary with perceived quality, with participants spending more time and exploring larger viewing angles for models receiving higher scores. These findings highlight the need for perceptually grounded, interaction-aware evaluation methodologies and provide guidelines for future perceptual optimization of 3D reconstruction pipelines.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Assessing the quality of 3D reconstructed models remains a key challenge in multimedia applications, especially in the context of cultural heritage, where visual fidelity and perceptual realism are equally crucial. This study investigates how reconstruction parameters, as well as existing objective quality metrics, align with human perception. In addition, we analyze how perceived quality and user interaction are related. A dataset of 3D models was generated by varying the number of input images, mesh complexity, and texture resolution. Results from a subjective study show that texture resolution significantly affects perceived quality, whereas variations in number of images and mesh complexity have a limited impact. Furthermore, interaction behavior was found to vary with perceived quality, with participants spending more time and exploring larger viewing angles for models receiving higher scores. These findings highlight the need for perceptually grounded, interaction-aware evaluation methodologies and provide guidelines for future perceptual optimization of 3D reconstruction pipelines.