A psychophysical study of fixation behavior in a computer game

Abstract

Prediction of gaze behavior in gaming environments can be a tremendously useful asset to game designers, enabling them to improve gameplay, selectively increase visual fidelity, and optimize the distribution of computing resources. The use of saliency maps is currently being advocated as the method of choice for predicting visual attention, crucially under the assumption that no specific task is present. This is achieved by analyzing images for low-level features such as motion, contrast, luminance, etc. However, the majority of computer games are designed to be easily understood and pose a task readily apparent to most players. Our psychophysical experiment shows that in a task-oriented context such as gaming, the predictive power of saliency maps at design time can be weak. Thus, we argue that a more involved protocol utilizing eye tracking, as part of the computer game design cycle, can be sufficiently robust to succeed in predicting fixation behavior of players.

Design and Application of Real-Time Visual Attention Model for the Exploration of 3D Virtual Environments

“…This suggests that, when an implicit task is involved during the navigation, users' attention seems more predictable thanks to a higher correlation with the top-down component controlling overall gaze direction [5] and including a task related weight. It also confirms Sundstedt et al [13] findings, suggesting that implementing a top-down component is highly beneficial for a visual attention model.…”

“…This suggests that visual attention models based only on a bottom-up or a top-down components would not be as effective at computing human attention as compared to using both components together. In other words, this confirms again the benefit of adding a top-down component to a visual attention model as stated in [13].…”

“…there is a strong correlation between gaze positions and salient areas in a saliency map. However, in a game scenario, Sundstedt et al [13] have shown that a saliency map alone is not sufficient to efficiently compute user's gaze. Even without an explicit task, users will automatically assume a task by themselves.…”

“…top-down, may choose a gaze position in this set. As a result, it seems necessary for a visual attention model to simulate both bottom-up and top-down components [13].…”

Modelling virtual camera behaviour through player gaze

“…Sundstedt et al [16] conducted an experimental study to analyse players' gaze behaviour during a maze puzzle solving game. The results of their experiment show that gaze movements, such as fixations, are mainly influenced by the game task.…”