There are important individual differences when experiencing VR setups. We ran a study with 20 participants who got a scale-matched avatar and were asked to blind-walk to a VR target placed 2.5 meters away. In such setups, people typically underestimate distances by approximately 10% when virtual environments are viewed through head mounted displays. Consistent with previous studies we found that the underestimation was significantly reduced the more embodied the participants were. However, not all participants developed the same level of embodiment when exposed to the exact same conditions

Abtahi, P

Gonzalez-Franco, M

Steed, A

English

UCL Discovery

Individual Differences in Embodied Distance Estimation in Virtual RealityMar Gonzalez-Franco∗Microsoft ResearchParastoo AbtahiStanford UniversityAnthony SteedMicrosoft ResearchUniversity College LondonAbstractThere are important individual differences when experiencing VRsetups. We ran a study with 20 participants who got ascale-matched avatar and were asked to blind-walk to a VR targetplaced 2.5 meters away. In such setups, people typicallyunderestimate distances by approximately 10% when virtualenvironments are viewed through head mounted displays.Consistent with previous studies we found that the underestimationwas significantly reduced the more embodied the participantswere. However, not all participants developed the same level ofembodiment when exposed to the exact same conditions.1 IntroductionSelf-avatar representation within the virtual environment is knownto have a wide variety of impacts on the user [21, 4, 2, 22]. Forexample, having a body, and more importantly, being encouragedto use it has a positive impact on reports of presence in virtualenvironments [20]. In a well-known study on locomotion,Usoh et al. compared real-walking to walking on the spot to flyingwith a joystick [24] and found that the subjective experience wassignificantly correlated with a sense of ownership over the virtualbody. Subsequently, the sense of ownership of a virtual body hasbeen extensively studied [9].When it comes to locomotion, it has been shown that thepresence of a self-avatar changes stepping behavior. In particular,if the feet are tracked, the self-avatar can be properly articulated inits gait. Lin et al. showed that the self-avatar animated by foottracking improved estimations of heights for stepping over andunder obstacles [12]. Similarly, Kim et al. found that the presenceof representations of the feet would lead to the users placing theirfeet more carefully [10].In this paper we further study the impact of embodied avatarsduring a distance estimation task inside VR [1].The ability to accurately convey distances through virtualenvironments is key to many potential applications: from veridicaltransfer of training through to ensuring fairness in competitivegames. As immersive VR is almost always experienced from afirst-person, egocentric point of view, it already benefits frommany cues that aid distance estimation: the eye-height can benaturally set at the correct height and the user can make naturalgestures. However, whenever studied, it is found that users ofvirtual environments tend to underestimate distances, and thuswhen asked to walk, they walk slightly shorter (e.g. see[14, 6, 23, 18]).Aside from the raw compression of distance, recently,Janeh et al. showed that a side-effect of motion compression seemsto be changes in gait [8]. Gait is thus one aspect of behaviour thatwe will study in our experiment.Prior work on embodiment has found that ownership over aself-avatar improves distance estimation, though the compressionis not completely removed [15, 19, 17]. However, control of the∗e-mail: margon@microsoft.comembodiment is important as the body is not just providing ameasure of scale for the avatar but also a way to interact with theavatar [16, 11].Our focus is to better understand the individual differences ofusers by analyzing their actual walking behaviour.2 Materials and MethodsTwenty participants (5 female, ages 25-55, µ = 34) with normalstereo vision participated in our experiment and received a giftcard as compensation.They wore a HTC Vive HMD, withhand-held controllers and trackers attached to their shoes. We usedthe Root Motion full-body inverse kinematics library to animate aDummy avatar. They were tracked with lighthouses and aTPCAST Wireless Adapter to enable an untethered VR experiencein our 2.8m x 4m x 2.8m study room. To guide the participantsalong a path in the room, we rendered a green X mark on theground and a capsule positioned at their eye height, as shown infigure 1.Figure 1: Participant walking towards a target before the distance es-timation task. Left) The avatar and the green target in the virtual city.Right) Participant holding the controllers while wearing the battery pack,wireless HMD, and foot trackers.The experiment followed this procedure:- 10 seconds of walking towards green targets. Once the targetis reached, the next target’s position is randomly generated withinthe physical room, providing the participant with a walkable pathin the virtual city.- After 10 seconds upon arrival to the target, the scene disappearsand is replaced by a white plane. A red target then appears at aprespecified distance from the Participant.- After 5 seconds, the red target disappears and the participantwalks in the empty scene to stop exactly where the red target was,and pull the trigger on the right-hand controller.- The virtual scene reappears and a new trial starts.The above sequence was repeated six times and the red target,positioned 2.5m away from the participant. At the end of theexperiment participants completed an embodiment questionnaireand the Nasa TLX questionnaire [5, 3].Individual StridesTime (seconds)Stride Length (cm)P1P2P13Normalized progression towards TargetOriginTarget1000255075Low EmbodiedHigh EmbodiedEmbodiment Score00.50.250.751-40%-20%0%20%*p=0.022t=2.4cor=0.49Distance Estimation Error (%)-10%10%-30%Embodiment Score (0 to 1)0 0.50.25 0.75 1Distance CompressionEmbodimentFigure 2: Walking behaviour changes for different avatar embodiment levels. For the individual strides we pick three participants (P2, high embodied,and P2,P13 low embodied) to be representatives because their cadence in steps is very comparable. Two main trends were identified for low embodiedparticipants the reduction of stride length (P1) or the reduction in the number of steps with a similar stride length (P13). In both cases the result was agreater distance compression for low embodied individuals.3 Results3.1 Embodiment AnalysisUsing Principal Component Analysis (PCA) we calculated theembodiment score of our participants [3] (Table 1). The averageembodiment score (normalized from 0 to 1) in our experiment was0.47± 0.14SD. Participants could be clustered into high embodied(0.59± 0.11 SD score) and low embodied (0.36± 0.06 SD score);the distributions in the two groups differed significantly(MannWhitney U = 0, n1 = n2 = 10, p < 0.0001).Table 1: PCA Factor LoadingsQuestionFactor 1EmbodiedFactor 2TaskI felt as if the virtual body was my body. 0.662 0.174It felt as if the virtual body I saw wassomeone else. -0.304The movements of the virtual body werecaused by my movement. 0.400I felt like I could control the virtual bodyas if it was my own body. 0.606 -0.119I felt as if the virtual body was moving byitself. -0.326I felt as if the movements of the virtual bodywere influencing my own movements. 0.584I felt as if my (real) body was turning intoan avatar body. 0.659 -0.168At some point it felt as if my real body wasstarting to take on the posture or shape of thevirtual body that I saw.0.729 0.110The task was mentally demanding. 0.196 0.784The task was physically demanding. 0.100 0.370The pace of the task felt hurried or rushed. -0.176 0.761I was successful at accomplishing what I wasasked to do. 0.350 -0.269I had to work hard to accomplish what I wasasked to do. 0.784I felt insecure, discouraged, irritated, stressed,and annoyed. -0.280 0.575Note: question loading with high influence on the component are in bold.3.2 Walking BehaviourThe distance error across all targets was 11 ± 0.54%, consistentwith previous findings in which people underestimated distancesin VR by 10% [7, 23]. We found a correlation betweenembodiment score and error for targets at more than 2m (Pearson,cor=0.49, t =2.4, df=18, p=0.025). High embodied participantssignificantly reduced their error to 5% while participants withlower embodiment maintained estimation errors over 10%.We analyzed the walking behavior to better understand theimproved estimation of distances for highly embodied participants.We found that low embodied participants stride length was0.6 ± 0.17 SD meters and the high embodied participants stridelength was 0.71 ± 0.1 SD meters (Welch test,t = −2.1,d f = 12.6, p = 0.05). The stride length was adjusted bythe participant’s height and then normalized to the equivalent of a1.7m tall person. We observed two main trends, (see Figure 2).The average number of steps across conditions was 5.28±1.57 forthe low embodied, and 4.97 ± 1.39 for the high embodied(p > 0.4). Neither the speed nor the cadence of the strides wereaffected by the embodiment level.4 DiscussionGiven the walking behavioural results, we hypothesize that mostlow embodied individuals were actually compressing the distanceto the target as a result of their reduced stride length. This stridecompression effect was consistent for the majority of the lowembodied participants, affecting 7 out of 10 participants. The restof the low embodied participants (3 out of 10) did not show shorterstrides, but rather a reduced number of steps that also translatedinto a distance estimation compression.These results, together with previous findings, have significantimplications for developers. For example, in collaborative VR,social clues are very important and users rely on implicittechniques such as proxemics or more directly distanceperceptions to interact [13]. Our work highlights that providing afirst person avatar might not be sufficient if the participants do notfeel embodied. We believe that to achieve highly effective VRapplications, individual perceptual differences need to beconsidered, as they ultimately translate into different behaviours inthe virtual environment, as shown by the gait analysis.We hypothesize that the behavioral alterations stemming fromindividual differences will have significant impact on other higher-level tasks such as navigation or social group forming.References[1] P. Abtahi, M. Gonzalez-Franco, E. Ofek, and A. Steed. Im a giant:Walking in large virtual environments at high speed gains. In Pro-ceedings of the 2019 CHI Conference on Human Factors in Comput-ing Systems. ACM, 2019.[2] M. Gonzalez-Franco and J. Lanier. Model of illusions and virtualreality. Frontiers in psychology, 8:1125, 2017.[3] M. Gonzalez-Franco and T. C. Peck. Avatar embodiment. towards astandardized questionnaire. Frontiers in Robotics and AI, 5:74, 2018.[4] M. Gonzalez-Franco, D. Perez-Marcos, B. Spanlang, and M. 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Individual differences in embodied distance estimation in virtual reality

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Individual differences in embodied distance estimation in virtual reality

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