STEREOSCOPIC IMAGE QUALITY IN VIRTUAL ENVIRONMENTS

被引:0
|
作者
Boehs, Gustavo [1 ]
Vieira, Milton L. H. [1 ]
机构
[1] Univ Fed Santa Catarina, BR-88040900 Florianopolis, SC, Brazil
来源
2014 INTERNATIONAL CONFERENCE ON 3D IMAGING (IC3D) | 2014年
关键词
stereoscopic; quality assessment; virtual environments;
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
The number of products capable of displaying stereoscopic (also known as 3D) images has been growing in recent years. The use of this technology has outgrown the silver screen and is now available in televisions, computers, tablets, and even cell phones. Due to its nature, content created for stereoscopic media requires attention in relation to some characteristics not present in the context of monoscopic media. With a focus on image creation, the objective of this research was to assess how different stereoscopic image generation methods can affect human perception. To achieve this a virtual environment was created and from it different videos were generated using various methods including converging cameras, parallel cameras, and depth image-based rendering (DIBR). These videos were shown to participants who assessed the picture quality, depth quality, and visual comfort of the media. It was found that there was very little difference between the perception of images generated by parallel and convergent cameras, while there was a substantial difference in terms of perception between these two types of image and DIBR images. Such results can significantly affect the choice of technology for stereoscopic image generation, influencing the production costs, the methods involved, and human and machine time consumption.
引用
收藏
页数:8
相关论文
共 50 条
  • [1] A framework for evaluating depth perception in stereoscopic virtual environments
    Silva, Sahra K. G.
    Correa, Cleber G.
    Lauretto, Marcelo S.
    Nunes, Fatima L. S.
    24TH SYMPOSIUM ON VIRTUAL AND AUGMENTED REALITY, SVR 2022, 2022, : 105 - 114
  • [2] Quality of Teaching in Virtual Environments
    Ardila Rodriguez, Mireya
    REVISTA VIRTUAL UNIVERSIDAD CATOLICA DEL NORTE, 2010, 30 : 63 - 84
  • [3] Subjective and Objective Quality Assessment for Stereoscopic Image Retargeting
    Fu, Zhenqi
    Shao, Feng
    Jiang, Qiuping
    Meng, Xiangchao
    Ho, Yo-Sung
    IEEE TRANSACTIONS ON MULTIMEDIA, 2021, 23 : 2100 - 2113
  • [4] Quality Assessment for Stereoscopic Image based on DCT frequency Information
    Sun, Chao
    Liu, Xingang
    Kang, Kai
    Yang, Laurence T.
    2013 12TH IEEE INTERNATIONAL CONFERENCE ON TRUST, SECURITY AND PRIVACY IN COMPUTING AND COMMUNICATIONS (TRUSTCOM 2013), 2013, : 1394 - 1398
  • [5] Stereoscopic Image Quality Assessment with The Dual-weight Model
    Zhu, Yucheng
    Zhai, Guangtao
    Gu, Ke
    Che, Zhaohui
    Li, Duo
    2016 IEEE INTERNATIONAL SYMPOSIUM ON BROADBAND MULTIMEDIA SYSTEMS AND BROADCASTING (BMSB), 2016,
  • [6] Stereoscopic Image Quality Assessment Based on both Distortion and Disparity
    Niu, Yuzhen
    Zhong, Yini
    Ke, Xiao
    Shi, Yiqing
    2018 IEEE INTERNATIONAL CONFERENCE ON VISUAL COMMUNICATIONS AND IMAGE PROCESSING (IEEE VCIP), 2018,
  • [7] Distortion of depth perception in virtual environments using stereoscopic displays: Quantitative assessment and corrective measures
    Kleiber, Michael
    Winkelholz, Carsten
    STEREOSCOPIC DISPLAYS AND APPLICATIONS XIX, 2008, 6803
  • [8] The Compressed Average Image Intensity metric for stereoscopic video quality assessment
    Wilczewski, Grzegorz
    PHOTONICS APPLICATIONS IN ASTRONOMY, COMMUNICATIONS, INDUSTRY, AND HIGH-ENERGY PHYSICS EXPERIMENTS 2016, 2016, 10031
  • [9] Blindly Evaluating Stereoscopic Image Quality with Free-Energy Principle
    Zhu, Yucheng
    Zhai, Guangtao
    Gu, Ke
    Liu, Min
    2016 IEEE INTERNATIONAL SYMPOSIUM ON CIRCUITS AND SYSTEMS (ISCAS), 2016, : 2222 - 2225
  • [10] Quality Assessment for High Dynamic Range Stereoscopic Omnidirectional Image System
    Cao, Liuyan
    Jiang, Hao
    Jiang, Zhidi
    You, Jihao
    Yu, Mei
    Jiang, Gangyi
    ADVANCED CONCEPTS FOR INTELLIGENT VISION SYSTEMS, ACIVS 2023, 2023, 14124 : 275 - 286