摘要：Tracking user’s visual attention is a fundamental aspect
in novel human-computer interaction paradigms
found in Virtual Reality. For example, multimodal interfaces
or dialogue-based communications with virtual
and real agents greatly benefit from the analysis of
the user’s visual attention as a vital source for deictic
references or turn-taking signals. Current approaches
to determine visual attention rely primarily on monocular
eye trackers. Hence they are restricted to the interpretation
of two-dimensional fixations relative to a
defined area of projection.
The study presented in this article compares precision,
accuracy and application performance of two
binocular eye tracking devices. Two algorithms are
compared which derive depth information as required
for visual attention-based 3D interfaces. This information
is further applied to an improved VR selection
task in which a binocular eye tracker and an adaptive
neural network algorithm is used during the disambiguation
of partly occluded objects.
