Novel haptic interface For viewing 3D images

In recent years there has been an explosion of devices and systems capable of displaying stereoscopic 3D images. While these systems provide an improved experience over traditional bidimensional displays they often fall short on user immersion. Usually these systems only improve depth perception by relying on the stereopsis phenomenon. We propose a system that improves the user experience and immersion by having a position dependent rendering of the scene and the ability to touch the scene. This system uses depth maps to represent the geometry of the scene. Depth maps can be easily obtained on the rendering process or can be derived from the binocular-stereo images by calculating their horizontal disparity. This geometry is then used as an input to be rendered in a 3D display, do the haptic rendering calculations and have a position depending render of the scene. The author presents two main contributions. First, since the haptic devices have a finite work space and limited resolution, we used what we call detail mapping algorithms. These algorithms compress geometry information contained in a depth map, by reducing the contrast among pixels, in such a way that it can be rendered into a limited resolution display medium without losing any detail. Second, the unique combination of a depth camera as a motion capturing system, a 3D display and haptic device to enhance user experience. While developing this system we put special attention on the cost and availability of the hardware. We decided to use only off-the-shelf, mass consumer oriented hardware so our experiments can be easily implemented and replicated. As an additional benefit the total cost of the hardware did not exceed the one thousand dollars mark making it affordable for many individuals and institutions

Stereoscopic high dynamic range imaging

Two modern technologies show promise to dramatically increase immersion in virtual environments. Stereoscopic imaging captures two images representing the views of both eyes and allows for better depth perception. High dynamic range (HDR) imaging accurately represents real world lighting as opposed to traditional low dynamic range (LDR) imaging. HDR provides a better contrast and more natural looking scenes. The combination of the two technologies in order to gain advantages of both has been, until now, mostly unexplored due to the current limitations in the imaging pipeline. This thesis reviews both fields, proposes stereoscopic high dynamic range (SHDR) imaging pipeline outlining the challenges that need to be resolved to enable SHDR and focuses on capture and compression aspects of that pipeline. The problems of capturing SHDR images that would potentially require two HDR cameras and introduce ghosting, are mitigated by capturing an HDR and LDR pair and using it to generate SHDR images. A detailed user study compared four different methods of generating SHDR images. Results demonstrated that one of the methods may produce images perceptually indistinguishable from the ground truth. Insights obtained while developing static image operators guided the design of SHDR video techniques. Three methods for generating SHDR video from an HDR-LDR video pair are proposed and compared to the ground truth SHDR videos. Results showed little overall error and identified a method with the least error. Once captured, SHDR content needs to be efficiently compressed. Five SHDR compression methods that are backward compatible are presented. The proposed methods can encode SHDR content to little more than that of a traditional single LDR image (18% larger for one method) and the backward compatibility property encourages early adoption of the format. The work presented in this thesis has introduced and advanced capture and compression methods for the adoption of SHDR imaging. In general, this research paves the way for a novel field of SHDR imaging which should lead to improved and more realistic representation of captured scenes

Utilization of EREP data in geological evaluation, regional planning, forest management, and water management in North Carolina

The author has identified the following significant results. The S190A, S190B, and S192 photographs and imagery were studied, using standard air-photo interpretation techniques supplemented by color additive viewing and density slicing. The EREP data were found to have potential usefulness for natural resource inventory work, water quality monitoring, and land use mapping for specific problems at scales up to 1:30,000. Distinctions between forest types in North Carolina are limited to conifers, mixed conifer-hardwoods, and hardwoods. Geologic interpretation was limited to detection of lineaments; lithologic differentiation and soil group mapping have proved infeasible in North Carolina except for differentiation of wetland soils in the coastal plain. Imagery from the S192 multispectral scanner has proved to be capable of useful discriminations for vegetation and crop analysis

Editable View Optimized Tone Mapping For Viewing High Dynamic Range Panoramas On Head Mounted Display

Head mounted displays are characterized by relatively low resolution and low dynamic range. These limitations significantly reduce the visual quality of photo-realistic captures on such displays. This thesis presents an interactive view optimized tone mapping technique for viewing large sized high dynamic range panoramas up to 16384 by 8192 on head mounted displays. This technique generates a separate file storing pre-computed view-adjusted mapping function parameters. We define this technique as ToneTexture. The use of a view adjusted tone mapping allows for expansion of the perceived color space available to the end user. This yields an improved visual appearance of both high dynamic range panoramas and low dynamic range panoramas on such displays. Moreover, by providing proper interface to manipulate on ToneTexture, users are allowed to adjust the mapping function as to changing color emphasis. The authors present comparisons of the results produced by ToneTexture technique against widely-used Reinhard tone mapping operator and Filmic tone mapping operator both objectively via a mathematical quality assessment metrics and subjectively through user study. Demonstration systems are available for desktop and head mounted displays such as Oculus Rift and GearVR

Change blindness: eradication of gestalt strategies

Arrays of eight, texture-defined rectangles were used as stimuli in a one-shot change blindness (CB) task where there was a 50% chance that one rectangle would change orientation between two successive presentations separated by an interval. CB was eliminated by cueing the target rectangle in the first stimulus, reduced by cueing in the interval and unaffected by cueing in the second presentation. This supports the idea that a representation was formed that persisted through the interval before being 'overwritten' by the second presentation (Landman et al, 2003 Vision Research 43149–164]. Another possibility is that participants used some kind of grouping or Gestalt strategy. To test this we changed the spatial position of the rectangles in the second presentation by shifting them along imaginary spokes (by ±1 degree) emanating from the central fixation point. There was no significant difference seen in performance between this and the standard task [F(1,4)=2.565, p=0.185]. This may suggest two things: (i) Gestalt grouping is not used as a strategy in these tasks, and (ii) it gives further weight to the argument that objects may be stored and retrieved from a pre-attentional store during this task

A luminance-contrast-aware disparity model and applications

Binocular disparity is one of the most important depth cues used by the human visual system. Recently developed stereo-perception models allow us to successfully manipulate disparity in order to improve viewing comfort, depth discrimination as well as stereo content compression and display. Nonetheless, all existing models neglect the substantial influence of luminance on stereo perception. Our work is the first to account for the interplay of luminance contrast (magnitude/frequency) and disparity and our model predicts the human response to complex stereo-luminance images. Besides improving existing disparity-model applications (e.g., difference metrics or compression), our approach offers new possibilities, such as joint luminance contrast and disparity manipulation or the optimization of auto-stereoscopic content. We validate our results in a user study, which also reveals the advantage of considering luminance contrast and its significant impact on disparity manipulation techniques.National Science Foundation (U.S.) (CGV-1111415