Inhibition of return in a 3D scene depends on the direction of depth switch between cue and target

被引:2
|
作者
Haponenko, Hanna [1 ]
Britt, Noah [1 ]
Cochrane, Brett [1 ]
Sun, Hong-jin [1 ]
机构
[1] McMaster Univ, Dept Psychol Neurosci & Behav, Hamilton, ON, Canada
基金
加拿大自然科学与工程研究理事会;
关键词
Inhibition of return; Spatial attention; Three-dimensional space; Virtual reality; OBJECT-CENTERED INHIBITION; SPATIAL ATTENTION; EYE; FACILITATION; PERCEPTION; COMPONENTS; LOCATIONS; MOVEMENTS; STIMULUS; SPREAD;
D O I
10.3758/s13414-024-02969-5
中图分类号
B84 [心理学];
学科分类号
04 ; 0402 ;
摘要
Inhibition of return (IOR) is a phenomenon that reflects slower target detection when the target appears at a previously cued rather than uncued location. In the present study, we investigated the extent to which IOR occurs in three-dimensional (3D) scenes comprising pictorial depth information. Peripheral cues and targets appeared on top of 3D rectangular boxes placed on the surface of a textured ground plane in virtual space. When the target appeared at a farther location than the cue, the magnitude of the IOR effect in the 3D condition remained similar to the values found in the two-dimensional (2D) control condition (IOR was depth-blind). When the target appeared at a nearer location than the cue, the magnitude of the IOR effect was significantly attenuated (IOR was depth-specific). The present findings address inconsistencies in the literature on the effect of depth on IOR and support the notion that visuospatial attention exhibits a near-space advantage even in 3D scenes consisting entirely of pictorial depth information.
引用
收藏
页码:2624 / 2642
页数:19
相关论文
共 50 条
  • [21] DYNAMIC SCENE DEPTH GENERATION METHOD FOR 2D TO 3D VIDEO CONVERSION
    Tsai, Tsung-Han
    Fan, Chen-Shuo
    Huang, Tai-Wei
    2015 IEEE INTERNATIONAL CONFERENCE ON CONSUMER ELECTRONICS - TAIWAN (ICCE-TW), 2015, : 340 - 341
  • [22] MagicMark: a marking menu using 2D direction and 3D depth information
    Fei Lyu
    Rui Xi
    Yuxin Han
    Yujie Liu
    Science China Information Sciences, 2018, 61
  • [23] MagicMark: a marking menu using 2D direction and 3D depth information
    Lyu, Fei
    Xi, Rui
    Han, Yuxin
    Liu, Yujie
    SCIENCE CHINA-INFORMATION SCIENCES, 2018, 61 (06)
  • [24] Dynamic 3D Scene Depth Reconstruction via Optical Flow Field Rectification
    Yang, You
    Liu, Qiong
    Ji, Rongrong
    Gao, Yue
    PLOS ONE, 2012, 7 (11):
  • [25] REGION-BASED DEPTH MAP CODING USING A 3D SCENE REPRESENTATION
    Maceira, M.
    Morros, J. R.
    Ruiz-Hidalgo, J.
    2015 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING (ICASSP), 2015, : 1235 - 1239
  • [26] Multi-view depth map sampling for 3D reconstruction of natural scene
    Jiang, Hangqing
    Zhao, Changfei
    Zhang, Guofeng
    Wang, Huiyan
    Bao, Hujun
    Jisuanji Fuzhu Sheji Yu Tuxingxue Xuebao/Journal of Computer-Aided Design and Computer Graphics, 2015, 27 (10): : 1805 - 1815
  • [27] Adaptive Depth Cue Adjustments of Interactive and Stereoscopic 3D Product Models for Design Education
    Chen, Li-Chieh
    Chu, Po-Ying
    Cheng, Yun-Maw
    HCI INTERNATIONAL 2015 - POSTERS' EXTENDED ABSTRACTS, PT I, 2015, 528 : 403 - 408
  • [28] DG-Recon: Depth-Guided Neural 3D Scene Reconstruction
    Ju, Jihong
    Tseng, Ching-Wei
    Bailo, Oleksandr
    Dikov, Georgi
    Ghafoorian, Mohsen
    2023 IEEE/CVF INTERNATIONAL CONFERENCE ON COMPUTER VISION (ICCV 2023), 2023, : 18138 - 18148
  • [29] Optimizing Placement of Commodity Depth Cameras for Known 3D Dynamic Scene Capture
    Chabra, Rohan
    Ilie, Adrian
    Rewkowski, Nicholas
    Cha, Young-Woon
    Fuchs, Henry
    2017 IEEE VIRTUAL REALITY (VR), 2017, : 157 - 166
  • [30] 3D Scene Mesh From CNN Depth Predictions And Sparse Monocular SLAM
    Mukasa, Tomoyuki
    Xu, Jiu
    Stenger, Bjorn
    2017 IEEE INTERNATIONAL CONFERENCE ON COMPUTER VISION WORKSHOPS (ICCVW 2017), 2017, : 912 - 919