# Eye-Tracking in Interactive Virtual Environments: Implementation and Evaluation
## 2 Methodological Issues
### The Complex World behind the Projection
The degree of complexity in recording and evaluating such movement increases significantly since the researcher abdicates control of the camera to the user, and thereby loses control of what is shown to the user, when it is shown, the order in which it is shown, from what angle and distance it is shown, and the overall scene composition. The user's ability to navigate through the virtual scene depends on the physical controller and how the physical controller translates into the virtual scene (in-engine character controller [53]), and how many degrees of freedom such a controller provides, i.e., whether the camera can be rotated and moved and the extent of this movement. Even with simple camera dynamics, the three-dimensionality of a scene, i.e., the virtual space coordinates at and from which the user looks, and the distance between the user camera and the _point of regard_, must be considered for eye-tracking evaluation purposes. Free movement of the camera may cause 3D objects to occlude other objects, creating difficulties in interpretation [54]. Given the rather low precision of VR eye-trackers, measurement artifacts can originate at the border of multiple neighboring objects. The depth irregularity of a 3D scene and the potential measurement error is also projected irregularly onto objects in the 3D scene (objects at greater/varying distances accumulate more absolute-distance measurement errors than near objects of similar size since the eye-tracking precision error is based on angles, and the absolute distances between angle-based raycasts increase with depth). This level of eye-tracking complexity in 3D VR has no parallel in traditional eye-tracking in 2D. _Level of interpretation complexity: eye movements over time with user movement and scene movement (synchronously)._
* **Dynamic camera, dynamic scene. ** All the interpretation issues mentioned above apply to this classification. In this case, other actors besides the user can also manipulate the projection and composition of the scene. At the user interaction level, these may be other (concurrent) user interfaces, controllers, or interaction metaphors, which allow selection, manipulation, systemic control, or symbolic input. Scene manipulation may occur at the level of individual objects, groups of objects [52], or the entire virtual scene [55]. At the execution level, events happening in the scene may be user-driven (interaction) or autonomous (AI or script-based), with or without feedback (visible, audible, or unregistrable), with or without affordances [56], (communicating or not communicating to the user that events or objects are potentially (inter)actible). Other users (multiplayer), AI, or interactive scripts may also instill changes within the scene. All these factors raise a new set of computational and visualization questions in the interpretation and visualization of a series of _point of regard_ coordinates that target moving objects (especially when the user is concurrently moving in a different direction, or using a different controller). _Level of interpretation complexity: eye movements over time with user movement and scene movement (asynchronously or a multitude of concurrent movements)._  
The examples as described above of a static, fixed user and a dynamic, moving user who observes a complex virtual scene, are depicted below in Figure 2, sourced from [PERSON] [37]. These examples do not consider the dynamics of the stimulus, regardless of whether it is a flat 2D video or an interactive multi-actor 3D scene. The movement diagram depicted by [PERSON] does not include other devices (e.g., motion controllers) with their own fields of reference. Beyond research interests and theoretical approaches, the potential and limitations of eye-tracking in VR are also applicable in practical implementation, i.e., in algorithms and the optimization, evaluation, and visualization of VR eye-tracking data in virtual 3D scenarios. Previous studies and implementations have considered this only to an extent.