Anna Ferrarotti

@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},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@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},

tppubtype = {article}

}