Occlusion Management in Conventional and Head-Mounted Display Visualization through the Relaxation of the Single Viewpoint/Timepoint Constraint
thesisposted on 2019-08-16, 16:48 authored by Meng-Lin WuMeng-Lin Wu
In conventional computer graphics and visualization, images are synthesized following the planar pinhole camera (PPC) model. The PPC approximates physical imaging devices such as cameras and the human eye, which sample the scene with linear rays that originate from a single viewpoint, i.e. the pinhole. In addition, the PPC takes a snapshot of the scene, sampling it at a single instant in time, or timepoint, for each image. Images synthesized with these single viewpoint and single timepoint constraints are familiar to the user, as they emulate images captured with cameras or perceived by the human visual system. However, visualization using the PPC model suffers from the limitation of occlusion, when a region of interest (ROI) is not visible due to obstruction by other data. The conventional solution to the occlusion problem is to rely on the user to change the view interactively to gain line of sight to the scene ROIs. This approach of sequential navigation has the shortcomings of (1) inefficiency, as navigation is wasted when circumventing an occluder does not reveal an ROI, (2) inefficacy, as a moving or a transient ROI can hide or disappear before the user reaches it, or as scene understanding requires visualizing multiple distant ROIs in parallel, and (3) user confusion, as back-and-forth navigation for systematic scene exploration can hinder spatio-temporal awareness.
In this thesis we propose a novel paradigm for handling occlusions in visualization based on generalizing an image to incorporate samples from multiple viewpoints and multiple timepoints. The image generalization is implemented at camera model level, by removing the same timepoint restriction, and by removing the linear ray restriction, allowing for curved rays that are routed around occluders to reach distant ROIs. The paradigm offers the opportunity to greatly increase the information bandwidth of images, which we have explored in the context of both desktop and head-mounted display visualization, as needed in virtual and augmented reality applications. The challenges of multi-viewpoint multi-timepoint visualization are (1) routing the non-linear rays to find all ROIs or to reach all known ROIs, (2) making the generalized image easy to parse by enforcing spatial and temporal continuity and non-redundancy, (3) rendering the generalized images quickly as required by interactive applications, and (4) developing algorithms and user interfaces for the intuitive navigation of the compound cameras with tens of degrees of freedom. We have addressed these challenges (1) by developing a multiperspective visualization framework based on a hierarchical camera model with PPC and non-PPC leafs, (2) by routing multiple inflection point rays with direction coherence, which enforces visualization continuity, and without intersection, which enforces non-redundancy, (3) by designing our hierarchical camera model to provide closed-form projection, which enables porting generalized image rendering to the traditional and highly-efficient projection followed by rasterization pipeline implemented by graphics hardware, and (4) by devising naturalistic user interfaces based on tracked head-mounted displays that allow deploying and retracting the additional perspectives intuitively and without simulator sickness.
- Doctor of Philosophy
- Computer Science
- West Lafayette