Explicit and Implicit Measures in Video Quality Assessment

被引:2
作者
Mele, Maria Laura [1 ,2 ,3 ]
Millar, Damon [1 ]
Rijnders, Christiaan Erik [1 ]
机构
[1] COGISEN Engn Co, Rome, Italy
[2] Univ Perugia, Dept Philosophy Social & Human Sci & Educ, Perugia, Italy
[3] Sapienza Univ, Interunivers Ctr Res Cognit Proc Nat & Art Syst, ECONA, Rome, Italy
来源
HUCAPP: PROCEEDINGS OF THE 14TH INTERNATIONAL JOINT CONFERENCE ON COMPUTER VISION, IMAGING AND COMPUTER GRAPHICS THEORY AND APPLICATIONS - VOL 2: HUCAPP | 2019年
关键词
Video Quality Assessment; Single Stimulus Assessment Methods; Psychophysiological Assessment of User Experience; UX; FRONTAL EEG ASYMMETRY; EYE-MOVEMENTS;
D O I
10.5220/0007396100380049
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
This work investigates the relation between subjective Video Quality Assessment (VQA) metrics and psychophysiological measures of human interaction assessment such as gaze tracking, electroencephalography and facial expression recognition. Subjective quality assessment is based on deliberate judgement attributions of perceived quality and processes that human perceivers are not consciously aware of. Traditional VQA methods ask participants to deliberately assign a quality score to videos in terms of the perceptual video quality. A methodology combining psychophysiological measures with traditional VQA methods is rarely used in the literature. This paper describes a model of video quality assessment which takes into account both explicit and implicit measures of subjective quality, by addressing two questions: (1) Do traditional video quality assessment methods correlate with unaware/implicit psychophysiological measures of quality perception assessment? (2) What can the main psychophysiological methods add to traditional video quality assessment? Findings show that (1) psychophysiological measures are able to measure differences of perceptual quality in compressed videos in terms of number of fixations and that (2) both VQA methods and psychophysiological assessment methods combined are able to provide additional information about cognitive and affective processes of attribution of the affective factors that underlie the attribution of quality.
引用
收藏
页码:38 / 49
页数:12
相关论文
共 50 条
  • [21] COME for No-Reference Video Quality Assessment
    Wang, Chunfeng
    Su, Li
    Zhang, Weigang
    IEEE 1ST CONFERENCE ON MULTIMEDIA INFORMATION PROCESSING AND RETRIEVAL (MIPR 2018), 2018, : 232 - 237
  • [22] TEXTURE INFORMATION BOOSTS VIDEO QUALITY ASSESSMENT
    Zhang, Ao-Xiang
    Wang, Yuan-Gen
    2022 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP), 2022, : 2050 - 2054
  • [23] CLIPVQA: Video Quality Assessment via CLIP
    Xing, Fengchuang
    Li, Mingjie
    Wang, Yuan-Gen
    Zhu, Guopu
    Cao, Xiaochun
    IEEE TRANSACTIONS ON BROADCASTING, 2025, 71 (01) : 291 - 306
  • [24] Video Quality Assessment With Serial Dependence Modeling
    Liu, Yongxu
    Wu, Jinjian
    Li, Aobo
    Li, Leida
    Dong, Weisheng
    Shi, Guangming
    Lin, Weisi
    IEEE TRANSACTIONS ON MULTIMEDIA, 2022, 24 : 3754 - 3768
  • [25] Video Quality Assessment for IPTV Services: A Survey
    Wang, Caihong
    Jiang, Xiuhua
    2012 7TH INTERNATIONAL CONFERENCE ON COMPUTING AND CONVERGENCE TECHNOLOGY (ICCCT2012), 2012, : 182 - 186
  • [26] Adaptive psychometric scaling for video quality assessment
    Menkovski, Vlado
    Liotta, Antonio
    SIGNAL PROCESSING-IMAGE COMMUNICATION, 2012, 27 (08) : 788 - 799
  • [27] Adversarial attacks on video quality assessment models
    Hu, Zongyao
    Liu, Lixiong
    Sang, Qingbing
    Wang, Chongwen
    KNOWLEDGE-BASED SYSTEMS, 2024, 293
  • [28] Salient Motion Features for Video Quality Assessment
    Culibrk, Dubravko
    Mirkovic, Milan
    Zlokolica, Vladimir
    Pokric, Maja
    Crnojevic, Vladimir
    Kukolj, Dragan
    IEEE TRANSACTIONS ON IMAGE PROCESSING, 2011, 20 (04) : 948 - 958
  • [29] A Survey on Recent Advances in Video Quality Assessment
    Yan J.-B.
    Fang Y.-M.
    Liu X.-L.
    Yao Y.-R.
    Sui X.-J.
    Jisuanji Xuebao/Chinese Journal of Computers, 2023, 46 (10): : 2196 - 2224
  • [30] REVISITING THE EFFICIENCY OF UGC VIDEO QUALITY ASSESSMENT
    Wang, Yilin
    Yim, Joong Gon
    Birkbeck, Neil
    Ke, Junjie
    Talebi, Hossein
    Chen, Xi
    Yang, Feng
    Adsumilli, Balu
    2022 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, ICIP, 2022, : 3016 - 3020