Virtual Task Environments Factors Explored in 3D Selection Studies

被引:1
作者
Bashar, Mohammad Raihanul [1 ]
Batmaz, Anil Ufuk [1 ]
机构
[1] Concordia Univ, Montreal, PQ, Canada
来源
PROCEEDINGS OF THE 50TH GRAPHICS INTERFACE CONFERENCE, GI 2024 | 2024年
关键词
Human-centered computing; Virtual Reality; Augmented Reality; 3D User Interfaces; 3D Selection; Virtual Task Environment; PASSIVE HAPTIC FEEDBACK; AUGMENTED REALITY; OBJECT SELECTION; TARGET SELECTION; PREDICTION ERROR; DESIGN; MANIPULATION; MANAGEMENT; REACH; DENSE;
D O I
10.1145/3670947.3670983
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In recent years, there has been a race among researchers, developers, engineers, and designers to come up with new interaction techniques for enhancing the performance and experience of users while interacting with virtual environments, and a key component of a 3D interaction technique is the selection technique. In this paper, we explore the environmental factors used in the assessment of 3D selection methods and classify each factor based on the task environment. Our approach consists of a thorough literature collection process, including four major Human-Computer Interaction repositories-Scopus, Science Direct, IEEE Xplore, and ACM Digital Library and created a dataset of a total of 277 papers. Drawing inspiration from the parameters outlined by LaViola et al. we manually classified each of those papers based on the task environment described in the papers. In addition, we explore the methodologies used in recent user studies to assess interaction techniques within various task environments, providing valuable insights into the developing landscape of virtual interaction research. We hope that the outcomes of our paper serve as a valuable resource for researchers, developers, and designers, providing a deeper understanding of task environments and offering fresh perspectives to evaluate their proposed 3D selection techniques in virtual environments.
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页数:16
相关论文
共 257 条
  • [1] Leveraging Passive Haptic Feedback in Virtual Environments with the Elastic-Arm Approach
    Achibet, Merwan
    Girard, Adrien
    Marchal, Maud
    Lecuyer, Anatole
    [J]. PRESENCE-TELEOPERATORS AND VIRTUAL ENVIRONMENTS, 2016, 25 (01) : 17 - 32
  • [2] Achibet M, 2015, P IEEE VIRT REAL ANN, P63, DOI 10.1109/VR.2015.7223325
  • [3] Ajaj Rami, 2009, P 2009 INT C MULT IN, P269, DOI [10.1145/1647314.1647372, DOI 10.1145/1647314.1647372]
  • [4] PAWdio: Hand Input for Mobile VR using Acoustic Sensing
    Al Zayer, Majed
    Tregillus, Sam
    Folmer, Eelke
    [J]. CHI PLAY 2016: PROCEEDINGS OF THE 2016 ANNUAL SYMPOSIUM ON COMPUTER-HUMAN INTERACTION IN PLAY, 2016, : 154 - 158
  • [5] Alex Marylyn, 2020, OzCHI '20: Proceedings of the 32nd Australian Conference on Human-Computer Interaction, P158, DOI 10.1145/3441000.3441054
  • [6] Nguyen A, 2015, P IEEE VIRT REAL ANN, P55, DOI 10.1109/VR.2015.7223324
  • [7] [Anonymous], 2012, ISO 9241-411:2012.
  • [8] [Anonymous], 2011, P 24 ANN ACM S USER
  • [9] [Anonymous], 2015, P 33 ANN ACM C HUM F, DOI DOI 10.1145/2702613.2732763
  • [10] Antonya Csaba., 2012, Accuracy of gaze point estimation in immersive 3D interaction interface based on eye tracking, P1125, DOI [10.1109/ICARCV.2012.6485315, DOI 10.1109/ICARCV.2012.6485315]