A Lightweight Tangible 3D Interface for Interactive Visualization of Thin Fiber Structures
IEEE Transactions on Visualization and Computer Graphics
Fig. 1. Left: Exploring fiber orientations in tissue using a paper prop and a commodity VR display. Middle: Linked views show: (1) a stereoscopic rendering of fibers; (2) a 3D fiber orientation histogram; and (3) 2D image slices. Note how only fibers oriented in the direction specified by the prop are rendered. Right: Patterns printed on the prop enable tracking of rolling and other gestures to provide a tangible 3D interface for the visualization. Abstract-We present a prop-based, tangible
... rface for 3D interactive visualization of thin fiber structures. These data are commonly found in current bioimaging datasets, for example second-harmonic generation microscopy of collagen fibers in tissue. Our approach uses commodity visualization technologies such as a depth sensing camera and low-cost 3D display. Unlike most current uses of these emerging technologies in the games and graphics communities, we employ the depth sensing camera to create a fish-tank stereoscopic virtual reality system at the scientist's desk that supports tracking of small-scale gestures with objects already found in the work space. We apply the new interface to the problem of interactive exploratory visualization of three-dimensional thin fiber data. A critical task for the visual analysis of these data is understanding patterns in fiber orientation throughout a volume.The interface enables a new, fluid style of data exploration and fiber orientation analysis by using props to provide needed passive-haptic feedback, making 3D interactions with these fiber structures more controlled. We also contribute a low-level algorithm for extracting fiber centerlines from volumetric imaging. The system was designed and evaluated with two biophotonic experts who currently use it in their lab. As compared to typical practice within their field, the new visualization system provides a more effective way to examine and understand the 3D bioimaging datasets they collect.