TY - GEN
T1 - Deep learning for objective quality assessment of 3D images
AU - Mocanu, Decebal Constantin
AU - Exarchakos, Georgios
AU - Liotta, Antonio
PY - 2014/1/28
Y1 - 2014/1/28
N2 - Improving the users' Quality of Experience (QoE) in modern 3D Multimedia Systems is a challenging proposition, mainly due to our limited knowledge of 3D image Quality Assessment algorithms. While subjective QoE methods would better reflect the nature of human perception, these are not suitable in real-time automation cases. In this paper we tackle this issue from a new angle, using deep learning to make predictions on the user's QoE rather than trying to measure it through deterministic algorithms. We benchmark our method, dubbed Quality of Experience for 3D images through Factored Third Order Restricted Boltzmann Machine (Q3D-RBM), with subjective QoE methods, to determine its accuracy for different types of 3D images. The outcome is a Reduced Reference QoE assessment process for automatic image assessment and has significant potential to be extended to work on 3D video assessment.
AB - Improving the users' Quality of Experience (QoE) in modern 3D Multimedia Systems is a challenging proposition, mainly due to our limited knowledge of 3D image Quality Assessment algorithms. While subjective QoE methods would better reflect the nature of human perception, these are not suitable in real-time automation cases. In this paper we tackle this issue from a new angle, using deep learning to make predictions on the user's QoE rather than trying to measure it through deterministic algorithms. We benchmark our method, dubbed Quality of Experience for 3D images through Factored Third Order Restricted Boltzmann Machine (Q3D-RBM), with subjective QoE methods, to determine its accuracy for different types of 3D images. The outcome is a Reduced Reference QoE assessment process for automatic image assessment and has significant potential to be extended to work on 3D video assessment.
KW - Deep learning
KW - Quality of experience
KW - Reduced reference 3D image quality assessment
KW - Third order restricted boltzmann machine
KW - Unsupervised learning
UR - http://www.scopus.com/inward/record.url?scp=84942648492&partnerID=8YFLogxK
U2 - 10.1109/ICIP.2014.7025152
DO - 10.1109/ICIP.2014.7025152
M3 - Conference contribution
AN - SCOPUS:84942648492
T3 - 2014 IEEE International Conference on Image Processing, ICIP 2014
SP - 758
EP - 762
BT - 2014 IEEE International Conference on Image Processing, ICIP 2014
PB - IEEE
CY - Piscataway, NJ
ER -