Visible surface ray-tracing of stereoscopic images

Adelson, Stephen J.; Hodges, Larry F.

doi:10.1145/503720.503778

Cited by 8 publications

(4 citation statements)

References 4 publications

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“…This means that a point may reproject to a position in the right view that is off from its true reprojection by as much as one-half a pixel. We have shown previously that for diffuse objects this difference is effectively insignificant (Adelson and Hodges 1992). However, when we add reflection and refraction, the color becomes more important.…”

Section: Reprojection Valuesa New Problemmentioning

confidence: 87%

“…By a more careful analysis of the situation specific to stereoscopic images, we have eliminated the filter and developed a more exact method for predicting the problem pixels after reprojection. Our current method eliminates the need to ray-trace up to 93% of the pixels in the right-eye view of a stereoscopic image (Devarajan and McAllister 1991;Adelson and Hodges 1992). Since then, we have extended the technique to include reflective and refractive objects.…”

Section: Previous Workmentioning

confidence: 99%

“…Our algorithm was implemented in a ray-tracer and used to test several scenes with diffuse objects and specular highlights, the full results and analysis of which appear in Adelson and Hodges (1992). All images consisted of 20 ellipsoids (40% spheres) of random size, positioning, and color.…”

Section: Performance Of Stereoscopic Visible-surface Ray-tracingmentioning

confidence: 99%

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Stereoscopic ray-tracing

Adelson

Hodges

1993

The Visual Computer

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In this paper, we describe a method to create an approximate ray-traced stereoscopic pair by transforming a fully raytraced left-eye view into an inferred righteye view. Performance results from evaluating several random scenes, which indicate that the second view in a stereoscopic image can be computed with as little as 5% of the effort required to fully ray-trace the first view, are presented. We also discuss worst-case performance of our algorithm and demonstrate that our technique is always at least as efficient as two passes of a standard ray-tracer.

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Section: Reprojection Valuesa New Problemmentioning

confidence: 87%

Section: Previous Workmentioning

confidence: 99%

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Stereoscopic ray-tracing

Adelson

Hodges

1993

The Visual Computer

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“…Spatial reprojection takes pixels in a source image and reprojects them into a target image [1]. Both of these images are associated with a different viewpoint (i.e., left and right eye for stereoscopic HMDs).…”

Section: Introductionmentioning

confidence: 99%

Real-time Stereoscopic Image-parallel Path Tracing

Leria,

Mäkitalo,

Jääskeläinen

2024

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Spatial reprojection can be utilized to lower the computational complexity of stereoscopic path tracing and reach real-time requirements. However it adds dependencies in the pipeline. We perform the handling of data dependencies through a task scheduler framework that embeds workload and dependency information at each stage of the pipeline. We propose a novel imageparallel stereoscopic path tracing pipeline, parallelizing the spatial reprojection stage, the hole-filling stage and post-processing algorithms (denoising, tonemapping) to multiple GPUs. Distributing the workload of the spatial reprojection stage to each GPU allows to locally detect the holes in the images, which are caused by non-reprojected pixels. For the spatial reprojection, denoising and hole-filling stages, we have respectively a speedup of ×2.75, ×4.2 and ×2.89 per GPU on animated scenes. Overall, our pipeline shows a speedup of ×2.25 compared to the open source state-of-the-art path tracer Tauray which only parallelizes path tracing.

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Selective rendering for efficient ray traced stereoscopic images

Chu

Debattista

et al. 2009

Vis Comput

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Depth-related visual effects are a key feature of many virtual environments. In stereo-based systems, the depth effect can be produced by delivering frames of disparate image pairs, while in monocular environments, the viewer has to extract this depth information from a single image by examining details such as perspective and shadows. This paper investigates via a number of psychophysical experiments, whether we can reduce computational effort and still achieve perceptually high quality rendering for stereo imagery. We examined selectively rendering the image pairs by exploiting the fusing capability and depth perception underlying human stereo vision. In ray tracing based global illumination systems, a higher image resolution introduces more computation to the rendering process since many more rays need to be traced. We first investigated whether we could utilise the human binocular fusing ability and significantly reduce the resolution of one of the image pairs and yet retain a high perceptual quality under stereo viewing condition. Secondly, we evaluated subjects' performance on a specific visual task that required accurate depth perception. We found that subjects required far fewer rendered depth cues in the stereo viewing environment to perform the task well. Avoiding rendering these detailed cues saved significant computational time. In fact it was possible to achieve a better task performance in the stereo viewing condition at a combined rendering time for the image pairs less than that required for the single monocular image. The outcome of this study suggests that we can produce more efficient stereo images for depth-related visual tasks by selective rendering and exploiting inherent features of human stereo vision.

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Visible surface ray-tracing of stereoscopic images

Cited by 8 publications

References 4 publications

Stereoscopic ray-tracing

Stereoscopic ray-tracing

Real-time Stereoscopic Image-parallel Path Tracing

Selective rendering for efficient ray traced stereoscopic images

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