However, little attention has been paid to the graphical model used to represent the self-avatar. However, the shape of the self-avatar does not seem to make any difference in such tasks. Thus, it is worth investigating whether a self-avatar is necessary for fidelity purposes in a virtual environment.
And, since different forms of self-avatar require different efforts to implement, it is also necessary to investigate whether the form of self-avatar can influence such loyalty in the virtual environment. In our work, we further investigated the factors that influence the usefulness of self-avatar judgments in the virtual environment. One of the most interesting questions is what factors can influence the influence of the self-avatar on coping judgments in the virtual environment.
It is well supported in social and behavioral studies that the shape of the self-avatar is important [Aymerich-Franch, Kizilcec, &.
Background
However, IVE technology has only recently evolved sufficiently to enable high-fidelity replication of the subject's body in virtual environments [Mohler et al., 2010]. This illusion has also recently been demonstrated in a virtual environment [Slater et al., 2007; Slater, Perez-Marcos, Ehrsson, & Sanchez-Vives, 2008]. In mixed reality, people's distance judgments change when they are induced to believe that their body size is changing [van der Hoort et al., 2011].
In virtual environments, people's judgments about affordability changed when the leg length of their self-avatar was adjusted [Lin et al., 2012]. Linkenauger and colleagues found that subjects' graspability judgments can be influenced when the visual hand of their self-avatar is scaled [Linkenauger et al., 2013]. Banakou et al., 2013] reported that subjects make different size judgments between a proportionally scaled self-avatar and a self-avatar scaled to a child's proportions, with subjects significantly overestimating size when using the child's avatar.
In the real world, humans are accurate in their perception of absolute distance, as evidenced by their performance of visually directed action [Loomis et al., 1992; Loomis et al., 1996; Rieser et al., 1990].
Experiment & Results
System setup
This subsystem tracked all tracking components worn by the subject in real time, while each component worn represented one body part of the subject (head, waist, right hand, left hand, right foot, and left foot). The Vicon detected both positions and orientations of all six body parts of the subject and sent this data to the MotionBuilder software. This subsystem mapped raw data received from Vicon to a virtual character and used inverse kinematics to generate the animation of the entire character in real time.
Inverse kinematics refers to the process of determining joint parameters that provide a desired position of the parts of the resulting character using a kinematics equation. This subsystem was used to track the head positions and orientations of the subjects, which were used for stance calculation. Since the Vicon can sometimes lose track of trackers, which can cause a very unattractive experience for the subjects if the stance is being tracked by Vicon, we felt it was necessary to use a separate tracking system solely for stance.
4 cameras were used to track the position of active LED markers, while the orientation was tracked by a built-in gyroscope. This subsystem took avatar character data from MotionBuilder as well as head positioning data from Precision Position Tracking to render the final virtual environment displayed in the HMD. All elements such as the final visible self-avatar, the room, the mirror, the edge and all the logical controls of the experiment were calculated in this subsystem.
Motion capture pipeline
The body dimensions data of the virtual character were set manually based on each subject's own body dimensions. Thus, the subjects' poses and positions were calculated, and the resulting data was packaged and streamed into the Vizard machine. The mean, slope, and false alarm rate values used in this procedure were all selected from our previous work [Lin, Rieser, &.
This algorithm took as input the subjects' decisions whether to step or not and converged on the subjects' threshold values. These decisions were recorded and used in the next iteration of the maximum likelihood procedure. The basic idea was to treat the mirror as a screen and place a virtual camera on the other side of the mirror.
In our study, the implementation of the mirror was considered in such a way that the subjects observed the entire mirrored environment from their original position. We believed that program performance could be optimized by mirroring objects with matrix operations. The first term translated the mirror to the world coordinate origin, while every other object added the same offset.
This subsystem took autonomous control of the avatars, and was terminated with the main program. When an error was found, the position and orientation of the head joint was bound to the viewpoint until the difference of two data from two machines came close again. This default avatar took data from MotionBuilder and was used as the template of the line avatar.
The midpoint, slope, and false alarm values we used in this study were chosen from our previous work with a similar experiment design [Lin et al., 2015]. Green [Green proposed an optimal p-goal that could be used to optimize the subject's threshold estimate, and this optimal p-goal was often called the sweet point. With all four equations presented above, our maximum likelihood procedure used in our experiments quickly converged to the subjects' threshold.
We used the average of the last four estimated thresholds for each subject to calculate the final result.
Experiment
Four males and two females experienced the no avatar condition, four males and two females experienced the line avatar condition, and three males and three females experienced the full avatar condition. The data from the resulting character was then transferred to a third machine running Vizard (Worldviz, Santa Barbara, CA) to render the immersive virtual environment and output the rendered image to a full-color stereo NVIS (Reston , VA) nVisor SX head mounted display (HMD). The experiment for each subject began with the subject reading the experimental instructions, after which we again explained the task procedures and answered questions verbally to ensure that the subject understood them.
Each self-avatar was calibrated to the same size as the subject: the avatar's leg length and arm length were calibrated to the subject's actual leg and arm lengths, and the avatar's eye height was calibrated to the subject's eye height. the person. For subjects in the full avatar condition: a gender-matched avatar model with a skin color that best represents the subject. For all subjects in the line avatar condition, a black line-based model representing the subject's skeleton was used.
And, for factor elimination reasons, even the subjects in the no-avatar condition could see no avatar, a default invisible avatar was used, and subjects were still asked to wear the same tracking device as others. In all three conditions, subjects experienced the IVE in first-person perspective and avatar was co-located with the participant. After the preparation and calibration were completed, subjects were asked to stand on the floor, in the center of our physical laboratory while wearing the HMD.
When the virtual environment first appeared, subjects were in a virtual room, standing on a wooden stage in the virtual room and facing a virtual mirror. Then, subjects in both the line-avatar condition and the full-avatar condition were given one minute to move around while observing their self-avatar both in first person and from the mirror to become familiar with the avatar. Subjects in the no-avatar condition were also asked to move around and observe the mirror, although they had no visual feedback about their body movement.
The subjects were able to move their body to observe and analyze the height, but no actual stepping action was performed. The HMD's screens went black for two seconds between every two trials to reduce the effect of previous experience on the subject's decision.
Results
Thus, the presence of the self-avatar significantly reduced the magnitude of the threshold, which is consistent with our previous work [Lin et al., 2015]. It is useful to qualitatively compare the mean thresholds in our result with our previous work. In our previous work, we used the same method but lacked a virtual mirror in the environment, and the mean threshold of the no-avatar condition was and the mean threshold of the whole-body avatar was.
Conclusion and discussion
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How presentation method and measurement protocol affect distance estimation in real and virtual environments. Paper presented at the Proceedings of the 5th symposium on Applied Perception in Graphics and Visualization, Los Angeles, California. The limited field of view of head-mounted displays is not the cause of distance underestimation in virtual environments.
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Analyzing the effect of geometric fidelity and motion of a virtual avatar on ego-centric spatial perception in immersive virtual environments. Paper presented at the Proceedings of the 16th ACM Symposium on Virtual Reality Software and Technology, Kyoto, Japan. Correcting distance estimates by interacting with immersive virtual environments: Effects of task and available sensory information.
Paper in the Proceedings of the 1st Symposium on Applied Perception in Graphics and Visualization. Paper presented in the proceedings of the CogSci06 symposium Toward Social Mechanisms of Android Science.
