Quality of Experience of multimedia content is investigated to understand the overall acceptability of the content as perceived by the end user. Recent perspectives stress the need to focus not only on perceptual aspects of the content but also on the interaction between perception and cognitive–emotional aspects. Our contribution lies on this direction by presenting a contactless approach to estimate heart rate variability by evaluating face skin color variations in a video sequence. The proposed framework allows to analyze long video sequences depicting a subject and it is robust with respect to small movements and illumination changes. The system is validated on a dataset of 64 sequences where users observe 3D movies selected to induce heart rate variations.

Bonomi, M., Battisti, F., Boato, G., Barreda-Angeles, M., Carli, M., Le Callet, P. (2019). Contactless approach for heart rate estimation for QoE assessment. SIGNAL PROCESSING-IMAGE COMMUNICATION, 78, 223-235 [10.1016/j.image.2019.07.004].

Contactless approach for heart rate estimation for QoE assessment

Battisti F.;Carli M.;Le Callet P.
2019

Abstract

Quality of Experience of multimedia content is investigated to understand the overall acceptability of the content as perceived by the end user. Recent perspectives stress the need to focus not only on perceptual aspects of the content but also on the interaction between perception and cognitive–emotional aspects. Our contribution lies on this direction by presenting a contactless approach to estimate heart rate variability by evaluating face skin color variations in a video sequence. The proposed framework allows to analyze long video sequences depicting a subject and it is robust with respect to small movements and illumination changes. The system is validated on a dataset of 64 sequences where users observe 3D movies selected to induce heart rate variations.
Bonomi, M., Battisti, F., Boato, G., Barreda-Angeles, M., Carli, M., Le Callet, P. (2019). Contactless approach for heart rate estimation for QoE assessment. SIGNAL PROCESSING-IMAGE COMMUNICATION, 78, 223-235 [10.1016/j.image.2019.07.004].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11590/364032
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