TY - GEN
T1 - Synthesis quality prediction model based on distortion intolerance
AU - Ryu, Seungchul
AU - Kim, Seungryong
AU - Sohn, Kwanghoon
N1 - Publisher Copyright:
© 2014 IEEE.
Copyright:
Copyright 2015 Elsevier B.V., All rights reserved.
PY - 2014/1/28
Y1 - 2014/1/28
N2 - Free-viewpoint video system will provide viewers with freedom to navigate through the scene at different viewpoints. In the system, arbitrary viewpoints of videos are synthesized by the depth image-based rendering with multi-view plus depth videos. Despite the widespread of technologies for free-viewpoint video system, the field of quality assessment for the free-viewpoint video, especially the quality prediction of a synthesized image, has not yet been thoroughly investigated. This paper analyzes how distortions in color and depth images influence on the quality of a synthesized image. Then, an objective quality prediction model for a synthesized image is proposed based on the concept of intolerance of synthesis distortion. Experimental results show that the proposed model provides outstanding performance in predicting the quality of a synthesized image compared to other models.
AB - Free-viewpoint video system will provide viewers with freedom to navigate through the scene at different viewpoints. In the system, arbitrary viewpoints of videos are synthesized by the depth image-based rendering with multi-view plus depth videos. Despite the widespread of technologies for free-viewpoint video system, the field of quality assessment for the free-viewpoint video, especially the quality prediction of a synthesized image, has not yet been thoroughly investigated. This paper analyzes how distortions in color and depth images influence on the quality of a synthesized image. Then, an objective quality prediction model for a synthesized image is proposed based on the concept of intolerance of synthesis distortion. Experimental results show that the proposed model provides outstanding performance in predicting the quality of a synthesized image compared to other models.
UR - http://www.scopus.com/inward/record.url?scp=84949927746&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84949927746&partnerID=8YFLogxK
U2 - 10.1109/ICIP.2014.7025117
DO - 10.1109/ICIP.2014.7025117
M3 - Conference contribution
AN - SCOPUS:84949927746
T3 - 2014 IEEE International Conference on Image Processing, ICIP 2014
SP - 585
EP - 589
BT - 2014 IEEE International Conference on Image Processing, ICIP 2014
PB - Institute of Electrical and Electronics Engineers Inc.
ER -