Modeling How User-Avatar Movement Inconsistency Affects the Sense of Body Ownership in Virtual Reality
Yukang Yan and Prof. Yuanchun Shi,
Tsinghua University Pervasive Computing Group, Beijing
Major revision by IMWUT'21 November round (second author)
March - September 2021
Team member (study design, user experiment, paper drafting)
An avatar mirroring the user’s movement is commonly adopted in Virtual Reality. Maintaining the user-avatar movement consistency provides the user a sense of body ownership and thus an immersive experience. However, breaking this consistency can enable new interaction functionalities, such as pseudo haptic feedback or input augmentation at the expense of immersion. We thus propose to quantify how the enlargement of movement inconsistency affects the body ownership.
We applied angular offsets to the avatar's shoulder and elbow joints and modeled their effects on the probability of the user noticing the inconsistency through a series of three user studies. Results show that the lost of body ownership increases roughly quadratically with stronger offsets and the probability distributions at two joints negatively affect each other. Leveraging the model, we implemented a technique that amplifies the user's arm movements with unnoticeable offsets and then evaluated implementations with diff parameters(offset strength, offset distribution). Results show that the technique with medium-level and balanced-distributed offsets achieves the best overall performance. Then we demonstrated our model's extendability with three VR applications including stroke rehabilitation, action game and widget arrangement.
Parameterization of a pose using the spherical polar coordinate system. We focused on angular offsets on the upper left limb.
We collected data on whether the participants noticed the user-avatar pose inconsistency. The noticeability of an offset is the number of participants that noticed the inconsistency.
Based on the model on static poses we proposed a dynamic virtual movement modification scheme that amplifies the user's movement while maintaining a sense of body ownership.
Our bottom-up approach in investigating influencing factors of offset noticeability. We investigated the strength of the offset on single axes, the direction of the offset, and finally the composite two-joint offset noticing probability.
Three applications with different user-avatar offsets: An rehabilitation application of creating illusion of motor performance improvement with high body ownership (left); A game application of changing physical effort demand by applying offsets (middle); A target selection application augmenting the user’s input and thus reducing the physical burden (right).