# Eye-Tracking in Interactive Virtual Environments: Implementation and Evaluation
## 2 Methodological Issues
### The Complex World behind the Projection
The specificity of processing and evaluating eye-tracking in 3D VR is dependent on the applied device(s), algorithm(s), and virtual environment(s). The transition to a virtual world is an extra calculation that traditional 2D eye-trackers need not be concerned about. The validity and feasibility of eye-tracking analysis in 3D VR therefore becomes complicated (a greater number of measured and intervening variables, and variable transition rules). This complexity has various degrees, however, and was first described by [PERSON] [37]: while a stationary eye-tracker needs only to observe eye movements, such movements in VR may be occurring in addition to or counter to the user's head or body movements (performed either directly, kinesthetically, or indirectly through a user interface), hand movements, user controller movements, interactions with other objects/users/entities in dynamic virtual scenes, and so on. A stationary eye-tracker with a chinrest only tracks the user's eyeballs, which move along two axes and have a limited angular range of rotation and can only be projectedagainst a fixed observed plane. Mobile eye-trackers may have to account for changing surroundings while the user moves about. Beyond the physical dimension, if a subject is rendered in VR, the projection must be converted, for example, by translation of the virtual coordinates into seemingly physical ones. Some stationary VR experiences have limited or no degrees of freedom, for example, 360 video or driving simulators [51]. Many VR devices, however, make full use of the mobility aspect to utilize the full potential of VR as a medium [52]. Eye-tracking in VR scenarios is therefore interpretation-heavy. Below is a description of the interpretation complexity in scenes when considering two control variables:  
* **Static camera, static scene**. The VR user observes the virtual world through a stationary, immovable virtual camera with zero degrees of freedom, and the only registered physical movement is eye movement. The user's eye movements have no dynamic or interactive function attached, effectively equating this interpretation level to that of traditional 2D eye-tracking with static stimuli and the user resting on a chinrest. This is the simplest eye-tracking interpretation level, as the _point of regard_ is the only relevant variable. The _point of fixation_ transition is unnecessary since all the virtual coordinates seen on the screen are the only coordinates there are. Even if the presented scene is a 3D visualization with varying depth, the _point of regard_ data set will always be transformed to the same _point of fixation_ data set, with 1:1 projection. The acquired data can therefore be reduced to _point of regard_ or worked with as if the stimulus were a static 2D image. _Level of interpretation complexity: eye coordinates over time._
* **Static camera, dynamic scene**. The user has no control over the virtual camera position or rotation, giving them no possibility to change the perspective from which the presented stimuli are seen. The experimental scene can, however, dynamically change in front of the user's eyes. In 3D, this would involve a predefined animation or other actors (AI, or other users with dynamic movement enabled). In classic eye-tracking studies, this can be equated to presenting a video. The majority of experimental control is still retained, i.e., the camera's rotation/position is shown through the virtual camera, but knowing which content is shown, and the order in which it is shown, depends on whether the dynamics are deterministic (e.g., predefined animation vs. another user with dynamic controls). Regardless, this type of scene must be evaluated frame-by-frame. In these types of continuous scene, the positions of objects and their AoI coordinates change in time. _Level of interpretation complexity: eye coordinates over time with scene movement._
* **Dynamic camera, static scene**. All interaction occurring in this type of scene is movement interaction [52], i.e., the user manipulates the virtual camera.