In this paper, we introduce a geometric design and fabrication framework for a family of interlocking space-filling shapes which we call bi-axial woven tiles. Our framework is based on a unique combination of (1) Voronoi partitioning of space using curve segments as the Voronoi sites and (2) the design of these curve segments based on weave patterns closed under symmetry operations. The underlying weave geometry provides an interlocking property to the tiles and the closure property under symmetry operations ensure single tile can fill space. In order to demonstrate this general framework, we focus on specific symmetry operations induced by bi-axial weaving patterns. We specifically showcase the design and fabrication of woven tiles by using the most common 2-fold fabrics called 2-way genus-1 fabrics, namely, plain, twill, and satin weaves.

In this paper, we develop a technique for placing informational labels in complex Virtual Environments (VEs). The ability to effectively and efficiently present labels in VEs is valuable in Virtual Reality (VR) for many reasons, but the motivation is to bring us closer to a system that delivers information in VR in an optimal way without causing information overload. The novelty of this technique lies in the use of eye tracking as an accurate indicator of attention to identifying objects of interest. Labels associated with such objects of interest are revealed when the user attends to them. We conduct a series of experiments to evaluate label placement based on user attention. This investigation is a first step toward integrating attention into information placement strategies in VR.

In this poster, we develop a technique for placing informational labels in complex Virtual Environments (VEs). The ability to effectively and efficiently present labels in VEs is valuable in Virtual Reality (VR) for many reasons, but the motivation is to bring us closer to a system that delivers information in VR in an optimal way without causing information overload. The novelty of this technique lies in the use of eye tracking as an accurate indicator of attention to identifying objects of interest. Labels associated with such objects of interest are revealed when the user attends to them. We conduct a series of experiments to evaluate label placement based on user attention. This attention is measured using eye tracking. Results show that one method in particular results in 100% accuracy in some scenarios in a search task with little difference in time taken to complete the task.