TY - GEN
T1 - A New 3D Video Database for Stereoscopic Video Comfortable Prediction
AU - Ma, Jian
AU - Li, Siyuan
AU - You, Zhixiang
AU - Shen, Liquan
AU - An, Ping
AU - Zhao, Xinxin
PY - 2020/10
Y1 - 2020/10
N2 - Visual comfortable is certainly one of the most critical issue in the research field of stereoscopic video. This is because that some viewers feel visual fatigue and discomfort when they see a wonderful stereoscopic video for a moment. Therefore, the problem of how to use related technologies to solve the series of problems exist in 3D comfortable prediction becomes urgent that we should settle. In this paper, we present a new three-dimensional (3D) video database (3DVID) for developing a new visual comfortable prediction technique of stereoscopic video. Specifically, this database contains 68 stereoscopic video pairs, where all of them are 1920×1080 resolution. The single stimulus continuous quality evaluation (SSCQE) method is adopted in our subjective tests, and the Mean Opinion Score (MOS) can be computed accordingly. In addition, we also show that the relationship between disparity, texture, motion and subjective MOS for each stereopair. Experimental results show that the proposed 3D video database contains a wide variety of scene variations and comfort levels, which is a very good benchmarking tool for 3D visual comfortable prediction algorithm design. © 2020 IEEE.
AB - Visual comfortable is certainly one of the most critical issue in the research field of stereoscopic video. This is because that some viewers feel visual fatigue and discomfort when they see a wonderful stereoscopic video for a moment. Therefore, the problem of how to use related technologies to solve the series of problems exist in 3D comfortable prediction becomes urgent that we should settle. In this paper, we present a new three-dimensional (3D) video database (3DVID) for developing a new visual comfortable prediction technique of stereoscopic video. Specifically, this database contains 68 stereoscopic video pairs, where all of them are 1920×1080 resolution. The single stimulus continuous quality evaluation (SSCQE) method is adopted in our subjective tests, and the Mean Opinion Score (MOS) can be computed accordingly. In addition, we also show that the relationship between disparity, texture, motion and subjective MOS for each stereopair. Experimental results show that the proposed 3D video database contains a wide variety of scene variations and comfort levels, which is a very good benchmarking tool for 3D visual comfortable prediction algorithm design. © 2020 IEEE.
KW - 3D video
KW - 3D video database
KW - SSCQE
KW - visual comfortable
UR - https://www.scopus.com/pages/publications/85101057932
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-85101057932&origin=recordpage
U2 - 10.1109/ICSIP49896.2020.9339460
DO - 10.1109/ICSIP49896.2020.9339460
M3 - RGC 32 - Refereed conference paper (with host publication)
T3 - IEEE International Conference on Signal and Image Processing, ICSIP
SP - 463
EP - 467
BT - 2020 IEEE 5th International Conference on Signal and Image Processing (ICSIP 2020)
PB - IEEE
T2 - 5th IEEE International Conference on Signal and Image Processing, ICSIP 2020
Y2 - 23 October 2020 through 25 October 2020
ER -