虚拟现实重定向行走中的场景缩放增益研究

doi:10.11996/JG.j.2095-302X.2025040793

图学学报 ›› 2025, Vol. 46 ›› Issue (4): 793-806.DOI: 10.11996/JG.j.2095-302X.2025040793

• 计算机图形学与虚拟现实 • 上一篇下一篇

虚拟现实重定向行走中的场景缩放增益研究

杜欣¹^,²(), 任洋甫¹^,²^,³(), 胥森哲⁴, 王巨宏⁵, 郑宇飞⁵, 张松海¹^,²^,³

1.青海大学计算机技术与应用学院，青海西宁 810016
2.青海省智能计算与应用实验室，青海西宁 810016
3.清华大学计算机科学与技术系，北京 100084
4.北京科技大学计算机与通信工程学院，北京 100084
5.深圳市腾讯计算机系统有限公司，广东深圳 518000

收稿日期:2024-10-05 修回日期:2025-02-06 出版日期:2025-08-30 发布日期:2025-08-11
通讯作者:任洋甫(1988-)，男，讲师，博士研究生。主要研究方向为计算机图形学与虚拟现实。E-mail：ryf21@mails.tsinghua.edu.cn
第一作者:杜欣(2000-)，女，硕士研究生。主要研究方向为虚拟现实。E-mail：du_xin2024@163.com
基金资助:
国家重点研发计划项目(2023YFF0905104);国家自然科学基金(62132012);国家自然科学基金(62402281);清华-腾讯互联网创新技术联合实验室项目

Investigation of scene scaling gains in redirected walking within virtual reality

DU Xin¹^,²(), REN Yangfu¹^,²^,³(), XU Senzhe⁴, WANG Juhong⁵, ZHENG Yufei⁵, ZHANG Songhai¹^,²^,³

1. College of Computer Technology and Application, Qinghai University, Xining Qinghai 810016, China
2. Qinghai Provincial Laboratory of Intelligent Computing and Applications, Xining Qinghai 810016, China
3. Department of Computer Science and Technology, Tsinghua University, Beijing 100084, China
4. School of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing 100084, China
5. Tencent Computer System Co., Ltd., Shenzhen Guangdong 518000, China

Received:2024-10-05 Revised:2025-02-06 Published:2025-08-30 Online:2025-08-11
First author：DU Xin (2000-), master student. Her main research interest covers virtual reality. E-mail：du_xin2024@163.com
Supported by:
National Key Research and Development Program of China(2023YFF0905104);National Natural Science Foundation of China(62132012);National Natural Science Foundation of China(62402281);Tsinghua-Tencent Joint Laboratory for Internet Innovation Technology Program

摘要/Abstract

摘要：

虚拟现实(VR)技术的不断发展为人们提供了沉浸式的体验，在虚拟环境(VE)中如何优化用户的感知和行走效率仍是一个亟需探讨的问题。基于此，通过用户实验探究了用户对VE中尺度变化的缩放增益感知阈值、用户对于场景缩小极限的接受度以及对场景缩放和平移增益叠加效应的接受度以优化VE的交互体验。首先，通过设置不同缩放增益下的虚拟场景让被试者执行目标跟随任务，收集并分析了3种场景下的被试者感知数据，发现被试者对VE尺度变化的缩放增益感知阈值存在一定的范围，虚拟场景的尺寸和环境中物体的密度等场景特性均显著影响被试者的缩放增益感知阈值。不同场景中，被试者对场景缩放的敏感度有显著差异，被试者的感知很大程度上依赖于场景本身的特性，虚拟场景的尺寸越小，环境内物体密度越高，则被试者的缩放增益感知阈值范围越窄。此外还通过李克特量表评估了被试者对场景极限缩小的接受度，发现过度缩小会显著降低被试者的舒适度并不利于被试者体验。实验结果表明，缩放增益与平移增益的叠加对用户感知影响较小，用户对此表现出低不适感和高接受度。

关键词: 虚拟现实, 重定向行走, 缩放增益, 感知阈值, 平移增益

Abstract:

The continuous advancement of virtual reality (VR) technology offers increasingly immersive experiences. However, optimizing user perception and walking efficiency in virtual environments (VE) remains a pressing challenge. This study conducted user experiments to investigate the perception threshold of scaling gain, user acceptance of extreme scene downscaling, and the combined effects of scaling and translational gains, aiming to enhance interaction experiences in virtual environments. First, subjects performed a target-following task in virtual scenes with varying scaling gains. Perception data was collected across three different scenarios, revealing a discernible range of perception thresholds for scaling gain. Scene characteristics, including virtual scene size and object density, significantly influenced the perception thresholds. Subjects demonstrated varying sensitivity to scaling gain across different scenarios, with smaller virtual environments and higher object density resulting in narrower perception threshold ranges. Additionally, a Likert scale was used to evaluate subject acceptance of extreme scene downscaling. The results indicated that excessive downscaling substantially reduced comfort and negatively impacted user experience. Furthermore, experiments on the combined effects of scaling and translational gains showed minimal impact on user perception, with participants reporting low discomfort and high acceptance of the combined gains.

Key words: virtual reality, redirected walking, scaling gain, perceptual thresholds, translation gain

中图分类号:

TP391.9

杜欣, 任洋甫, 胥森哲, 王巨宏, 郑宇飞, 张松海. 虚拟现实重定向行走中的场景缩放增益研究[J]. 图学学报, 2025, 46(4): 793-806.

DU Xin, REN Yangfu, XU Senzhe, WANG Juhong, ZHENG Yufei, ZHANG Songhai. Investigation of scene scaling gains in redirected walking within virtual reality[J]. Journal of Graphics, 2025, 46(4): 793-806.

图/表 14

图1 场景俯视图((a) 场景1；(b) 场景2；(c) 场景3)

Fig. 1 Overhead view of the scenes ((a) Scene 1; (b) Scene 2; (c) Scene 3)

图2 场景透视图((a) 场景1；(b) 场景2；(c) 场景3)

Fig. 2 Perspective view of the scenes ((a) Scene 1; (b) Scene 2; (c) Scene 3)

图3 实验场地及被试者((a) 缩放增益为1.1；(b) 缩放增益为0.3)

Fig. 3 Experimental setting and participants ((a) With a scaling gain of 1.1; (b) With a scaling gain of 0.3)

图4 实验1流程图

Fig. 4 Flowchart of experiment 1

图5 实验2流程图

Fig. 5 Flowchart of experiment 2

图6 实验3流程图

Fig. 6 Flowchart of experiment 3

图7 缩放增益感知概率分布

Fig. 7 Scaling gain perception probability distribution

表1 个体心理测量函数结果

Table 1 Individual psychological measurement function results

被试者		场景1			场景2			场景3
被试者		25%	PSE	75%	25%	PSE	75%	25%	PSE	75%
男	1	0.699	0.902	1.110	0.977	1.030	1.080	1.010	1.050	1.090
	2	0.930	1.000	1.070	1.020	1.070	1.120	1.080	1.090	1.100
	3	0.966	1.150	1.340	0.909	0.978	1.050	0.995	1.070	1.140
	4	0.864	0.985	1.110	0.963	1.060	1.150	1.050	1.050	1.050
	5	1.150	1.320	1.500	0.990	1.050	1.110	1.010	1.050	1.090
	6	1.070	1.070	1.070	1.020	1.110	1.190	0.951	1.000	1.060
	7	0.930	1.000	1.070	0.943	1.020	1.100	1.010	1.050	1.090
	8	0.853	0.922	0.991	0.900	0.911	0.922	0.977	1.030	1.080
	9	0.795	0.883	0.971	1.020	1.070	1.120	1.020	1.070	1.120
	10	0.948	1.030	1.120	0.909	0.978	1.050	1.010	1.050	1.090
女	1	0.859	0.950	1.040	1.180	1.230	1.280	1.110	1.150	1.190
	2	0.878	0.944	1.010	1.020	1.020	1.020	0.977	0.989	1.000
	3	0.809	0.906	1.000	1.010	1.100	1.190	0.969	1.070	1.180
	4	0.788	0.800	0.812	0.890	0.900	0.910	0.988	1.000	1.010
	5	0.818	0.905	0.993	0.990	1.050	1.110	1.250	1.250	1.250
	6	0.681	0.780	0.878	0.961	1.030	1.090	1.000	1.010	1.020
	7	0.717	0.805	0.893	0.997	1.090	1.190	1.010	1.050	1.090
	8	1.290	1.460	1.620	0.842	0.895	0.949	0.881	0.891	0.900
	9	0.908	0.950	0.992	0.946	0.950	0.953	1.140	1.140	1.140
	10	0.694	0.783	0.871	0.934	1.040	1.140	1.100	1.110	1.120
男性平均		0.885	1.020	1.160	0.953	1.030	1.110	1.000	1.050	1.100
女性平均		0.775	0.928	1.080	0.945	1.040	1.130	0.989	1.070	1.150
全体平均		0.827	0.977	1.130	0.949	1.030	1.120	0.993	1.060	1.120

图8 全体被试者在不同场景下的阈值变化趋势

Fig. 8 Threshold variation trend of all subjects in different scenes

图9 男性被试者在不同场景下的阈值变化趋势

Fig. 9 Threshold variation trend of male subjects in different scenes

图10 女性被试者在不同场景下的阈值变化趋势

Fig. 10 Threshold variation trend of female subjects in different scenes

图11 被试者接受度占比

Fig. 11 Subject acceptance proportion

图12 不同缩放增益下的SSQ得分情况

Fig. 12 SSQ scores under different scaling gains

图13 增益叠加研究数据分析

Fig. 13 Data analysis of gain stacking research

参考文献 37

[1]	SPARKES M. What is a metaverse[J]. New Scientist, 2021, 251(3348): 18.
[2]	RAZZAQUE S, KOHN Z, WHITTON M C. Redirected walking[EB/OL]. [2024-04-04]. https://www.cs.unc.edu/techreports/01-007.pdf.
[3]	ZHANG S H, CHEN C H, ZOLLMANN S. One-step out-of-place resetting for redirected walking in VR[J]. IEEE Transactions on Visualization and Computer Graphics, 2023, 29(7): 3327-3339.
[4]	KRUSE L, LANGBEHN E, STEINICKE F. I can see on my feet while walking: sensitivity to translation gains with visible feet[C]// 2018 IEEE Conference on Virtual Reality and 3D User Interfaces. New York: IEEE Press, 2018: 305-312.
[5]	WILLIAMS N L, PECK T C. Estimation of rotation gain thresholds considering FOV, gender, and distractors[J]. IEEE Transactions on Visualization and Computer Graphics, 2019, 25(11): 3158-3168.
[6]	RIETZLER M, GUGENHEIMER J, HIRZLE T, et al. Rethinking redirected walking: on the use of curvature gains beyond perceptual limitations and revisiting bending gains[C]// 2018 IEEE International Symposium on Mixed and Augmented Reality. New York: IEEE Press, 2018: 115-122.
[7]	XU S Z, CHEN F X Y, GONG R, et al. BiRD: using bidirectional rotation gain differences to redirect users during back-and-forth head turns in walking[J]. IEEE Transactions on Visualization and Computer Graphics, 2024, 30(5): 2693-2702.
[8]	KIM D, KIM J, SHIN J E, et al. Effects of virtual room size and objects on relative translation gain thresholds in redirected walking[C]// 2022 IEEE Conference on Virtual Reality and 3D User Interfaces. New York: IEEE Press, 2022: 379-388.
[9]	WANG L W, CAI S Y, SANDOR C. Perceptual thresholds of visual size discrimination in augmented and virtual reality[J]. Computers & Graphics, 2023, 117: 105-113.
[10]	HÉBERT-LAVOIE M, DOYON-POULIN P, OZELL B. Identification of visual functional thresholds for immersion assessment in virtual reality[J]. PRESENCE: Virtual and Augmented Reality, 2020, 29: 1-22.
[11]	KIM D, KIM S, SHIN J E, et al. The effects of spatial configuration on relative translation gain thresholds in redirected walking[J]. Virtual Reality, 2023, 27(2): 1233-1250.
[12]	RAZZAQUE S. Redirected walking[D]. Chapel Hill: The University of North Carolina at Chapel Hill, 2005.
[13]	LI Y J, STEINICKE F, WANG M. A comprehensive review of redirected walking techniques: taxonomy, methods, and future directions[J]. Journal of Computer Science and Technology, 2022, 37(3): 561-583.
[14]	LANGBEHN E, STEINICKE F. Redirected walking in virtual reality[M]//LEE N. Encyclopedia of Computer Graphics and Games. Cham: Springer, 2018: 26-27.
[15]	LANGBEHN E, LUBOS P, BRUDER G, et al. Application of redirected walking in room-scale VR[C]// 2017 IEEE Virtual Reality. New York: IEEE Press, 2017: 449-450.
[16]	SRA M, XU X H, MOTTELSON A, et al. VMotion: designing a seamless walking experience in VR[C]// 2018 Designing Interactive Systems Conference. New York: ACM, 2018: 59-70.
[17]	SUN Q, PATNEY A, WEI L Y, et al. Towards virtual reality infinite walking: dynamic saccadic redirection[J]. ACM Transactions on Graphics (TOG), 2018, 37(4): 67.
[18]	周强, 张敏雄, 吴新丽, 等. 体感交互虚拟漫游的沉浸感评价[J]. 图学学报, 2020, 41(3): 342-349. DOI
	ZHOU Q, ZHANG M X, WU X L, et al. Immersion evaluation of virtual roaming with proprioceptive interaction[J]. Journal of Graphics, 2020, 41(3): 342-349 (in Chinese). DOI
[19]	INTERRANTE V, RIES B, ANDERSON L. Seven league boots: a new metaphor for augmented locomotion through moderately large scale immersive virtual environments[C]// 2007 IEEE Symposium on 3D User interfaces. New York: IEEE Press, 2007.
[20]	ABTAHI P, GONZALEZ-FRANCO M, OFEK E, et al. I’m a giant: walking in large virtual environments at high speed gains[C]// 2019 CHI Conference on Human Factors in Computing Systems. New York: ACM, 2019: 522.
[21]	CARDOSO J C S, PERROTTA A. A survey of real locomotion techniques for immersive virtual reality applications on head-mounted displays[J]. Computers & Graphics, 2019, 85: 55-73.
[22]	XU S Z, HUANG K, FAN C W, et al. Spatial contraction based on velocity variation for natural walking in virtual reality[J]. IEEE Transactions on Visualization and Computer Graphics, 2024, 30(5): 2444-2453.
[23]	STEINICKE F, BRUDER G, JERALD J, et al. Estimation of detection thresholds for redirected walking techniques[J]. IEEE Transactions on Visualization and Computer Graphics, 2010, 16(1): 17-27. DOI PMID
[24]	马明明, 业全, 胡杨, 等. 头部旋转重定向的交互效率和眩晕感研究[J]. 图学学报, 2019, 40(3): 452-459. DOI
	MA M M, YE Q, HU Y, et al. Research on the interaction efficiency and vertigo sensation of head rotation[J]. Journal of Graphics, 2019, 40(3): 452-459 (in Chinese).
[25]	TIRADO CORTES C A, CHEN H T, LIN C T. Analysis of VR sickness and gait parameters during non-isometric virtual walking with large translational gain[C]// The 17th International Conference on Virtual-Reality Continuum and its Applications in Industry. New York: ACM, 2019: 16.
[26]	STEINICKE F, BRUDER G, ROPINSKI T, et al. Moving towards generally applicable redirected walking[EB/OL]. [2024-04-04]. https://www.uni-ulm.de/fileadmin/website_uni_ulm/iui.inst.100/institut/Papers/viscom/2008/moving_towards.pdf#:-:text=In%20this%20paper%20we%20present%20an%20evaluation%20of,the%20design%20process%20of%20a%20virtual%20locomotion%20interface.
[27]	NITZSCHE N, HANEBECK U D, SCHMIDT G. Motion compression for telepresent walking in large target environments[J]. Presence, 2004, 13(1): 44-60.
[28]	GREEN D M, SWETS J A. Signal detection theory and psychophysics[M]. New York: Wiley, 1966: 61-62.
[29]	HAUTUS M J, MACMILLAN N A, CREELMAN C D. Detection theory: a user’s guide[M]. 3rd ed. New York: Routledge, 2021: 89-90.
[30]	GRECHKIN T, THOMAS J, AZMANDIAN M, et al. Revisiting detection thresholds for redirected walking: combining translation and curvature gains[C]// The ACM Symposium on Applied Perception. New York: ACM, 2016: 113-120.
[31]	MEYER F, NOGALSKI M, FOHL W. Detection thresholds in audio-visual redirected walking[EB/OL]. [2024-04-04]. https://tore.tuhh.de/entities/publication/cd50e637-b253-4493-a107-ca55d636901c#:-:text=In%20this%20paper%20an%20experiment%20to%20measure%20the,the%20results%20are%20presented%20and%20compared%20to%20pre.
[32]	ZHANG J X, LANGBEHN E, KRUPKE D, et al. Detection thresholds for rotation and translation gains in 360° video-based telepresence systems[J]. IEEE Transactions on Visualization and Computer Graphics, 2018, 24(4): 1671-1680.
[33]	SELZER M N, LARREA M L, CASTRO S M. Analysis of translation gains in virtual reality: the limits of space manipulation[J]. Virtual Reality, 2022, 26(4): 1459-1469.
[34]	LUO E X, TANG K Y, XU S Z, et al. Walking telescope: exploring the zooming effect in expanding detection threshold range for translation gain[C]// The 12th International Conference on Computational Visual Media. Cham: Springer, 2024: 252-273.
[35]	KENNEDY R S, LANE N E, BERBAUM K S, et al. Simulator sickness questionnaire: an enhanced method for quantifying simulator sickness[J]. The International Journal of Aviation Psychology, 1993, 3(3): 203-220.
[36]	WANG C, ZHANG S H, ZHANG Y Z, et al. On rotation gains within and beyond perceptual limitations for seated VR[J]. IEEE Transactions on Visualization and Computer Graphics, 2023, 29(7): 3380-3391.
[37]	SANAEI M, GILBERT S B, JAVADPOUR N, et al. The correlations of scene complexity, workload, presence, and cybersickness in a task-based VR game[C]// International Conference on Human-Computer Interaction. Cham: Springer, 2024: 277-289.

虚拟现实重定向行走中的场景缩放增益研究

Investigation of scene scaling gains in redirected walking within virtual reality

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