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Your search keyword '"Barreda-Angeles, M."' showing total 3 results
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3 results on '"Barreda-Angeles, M."'

2. Quality of experience and quality of service metrics for 3D content

Author

Barreda-Ángeles, Miguel, Battisti, Federica, Boato, Giulia, Carli, Marco, Dumic, Emil, Gelautz, Margrit, Hewage, Chaminda, Kukolj, Dragan, Le-Callet, Patrick, Liotta, Antonio, Pasquini, Cecilia, Pereda-Baños, Alexandre, Politis, Christos, Sandic, Dragana, Tekalp, Murat, Torres-Vega, María, Zlokolica, Vladimir, Assunção, P., Gotchev, A., Electro-Optical Communication, Barreda-Angeles, M., Battisti, F., Boato, G., Carli, M., Dumic, E., Gelautz, M., Hewage, C., Kukolj, D., Le-Callet, P., Liotta, A., Pasquini, C., Pereda-Banos, A., Politis, C., Sandic, D., Tekalp, M., Torres-Vega, M., Zlokolica, V., Laboratoire des Sciences du Numérique de Nantes (LS2N), Université de Nantes - UFR des Sciences et des Techniques (UN UFR ST), Université de Nantes (UN)-Université de Nantes (UN)-École Centrale de Nantes (ECN)-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT), Image Perception Interaction (IPI), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Université de Nantes - UFR des Sciences et des Techniques (UN UFR ST), Barcelona Media [Barcelona] (BM), Digital Signal Processing Multimedia & Optical Communications Laboratory [Rome] (COMLAB), Università degli Studi Roma Tre, Wireless Multimedia & Networking (WMN) Res. Group, Kingston Univ., London, UK, Kingston University, University of Novi Sad, Universität Innsbruck [Innsbruck], Koç University, IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), and Université de Nantes (UN)-Université de Nantes (UN)-École Centrale de Nantes (ECN)-Centre National de la Recherche Scientifique (CNRS)

Subjects
Transmission delay, Multimedia, Computer science, media_common.quotation_subject, Quality of service, Latency (audio), 020206 networking & telecommunications, Throughput, 02 engineering and technology, computer.software_genre, [INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV], 0202 electrical engineering, electronic engineering, information engineering, Bandwidth (computing), 020201 artificial intelligence & image processing, Quality (business), Quality of experience, computer, ComputingMilieux_MISCELLANEOUS, media_common, Jitter
Abstract

Traditionally, the quality of a multimedia system was mainly assessed through the evaluation of its Quality of Service (QoS) that is by evaluating system parameters such as bandwidth, latency, jitter, throughput, transmission delay, availability, etc. However, these metrics often failed to capture the actual end-user perceived quality, which has prompted the development of the construct of Quality of Experience (QoE), widely understood as an interaction of the technical features of multimedia systems with perceptual, and cognitive/emotional factors involved in the interpretation of those features by users. This chapter addresses the open issues in the field of QoS and QoE assessments. First, the perceptual characteristics of the multiview content are analyzed, and then a survey on the existing approaches for QoS and QoE estimation is performed. The analysis is then focused on the subjective aspects of QoE assessment, by describing the standard methodologies currently used and new trends based on human factors research. Finally, the chapter offers a few guidelines for future research directions in the field.

Published
2019
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3. Contactless approach for heart rate estimation for QoE assessment

Author

Marco Carli, Federica Battisti, Miguel Barreda-Ángeles, Mattia Bonomi, Patrick Le Callet, Giulia Boato, Digital Signal Processing Multimedia & Optical Communications Laboratory [Rome] (COMLAB), Università degli Studi Roma Tre, Barcelona Media [Barcelona] (BM), Laboratoire des Sciences du Numérique de Nantes (LS2N), IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Université de Nantes - UFR des Sciences et des Techniques (UN UFR ST), Université de Nantes (UN)-Université de Nantes (UN)-École Centrale de Nantes (ECN)-Centre National de la Recherche Scientifique (CNRS), Image Perception Interaction (IPI), Université de Nantes (UN)-Université de Nantes (UN)-École Centrale de Nantes (ECN)-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Bonomi, M., Battisti, F., Boato, G., Barreda-Angeles, M., Carli, M., Le Callet, P., Université de Nantes - UFR des Sciences et des Techniques (UN UFR ST), and Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)

Subjects
Computer science, media_common.quotation_subject, 3D video, Heart rate estimation, Heart rate variability, Quality of experience, 02 engineering and technology, Perception, Heart rate, 0202 electrical engineering, electronic engineering, information engineering, Computer vision, Electrical and Electronic Engineering, ComputingMilieux_MISCELLANEOUS, media_common, Estimation, Focus (computing), business.industry, End user, 020206 networking & telecommunications, Face (geometry), [INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV], Signal Processing, 020201 artificial intelligence & image processing, Computer Vision and Pattern Recognition, Artificial intelligence, business, Software
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.

Published
2019
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