Multi-perspective stereoscopy from light fields

KimChangil,; HornungAlexander,; HeinzleSimon,; MatusikWojciech,; GrossMarkus,

doi:10.1145/2070781.2024224

Cited by 55 publications

(18 citation statements)

References 35 publications

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“…The adaptation of stereoscopic content to a disparity range that provides a comfortable viewing experience has motivated a number of recent works that focus on disparity retargeting [Lang et al 2010;Kim et al 2011;Masia et al 2013;Kellnhofer et al 2013]. …”

Section: Stereoscopic Retargetingmentioning

confidence: 99%

A metric of visual comfort for stereoscopic motion

Masiá

et al. 2013

ACM Trans. Graph.

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0 5 10 15 20 0 0.5 1 1.5 2 0 0.5 1 1.5 2 2.5 3 Vz [d eg /s ec ] V x y [d e g /s e c ] Vz [deg/sec] C=3 C=4 Comfortable Uncomfortable disparity [deg] 0 0.5 1 1.5 2 2.5 3 Vxy=8 0 0.5 1 1.5 2 Frame 8 Frame 23 Frame 129 Mr Mp Left Figure 1: Our novel metric of visual comfort for stereoscopic content takes into account disparity, motion in depth, motion on the screen plane, and the spatial frequency of luminance contrast. Based on our measured comfort function, we derive a metric to predict the degree of comfort for short stereoscopic videos. Left: Example slice of the comfort zone computed by our comfort function for a spatial frequency of 1cpd (bounded by comfort values of 3 and 4). Right: comfort maps computed using our metric on three representative frames of the bunny movie ( c Blender Foundation). From top to bottom, input frames, per-pixel results, and per-region results (brighter red indicates less comfort). Our metric predicts less comfort with faster movement (frame 23), in agreement with the perceptual experiments. AbstractWe propose a novel metric of visual comfort for stereoscopic motion, based on a series of systematic perceptual experiments. We take into account disparity, motion in depth, motion on the screen plane, and the spatial frequency of luminance contrast. We further derive a comfort metric to predict the comfort of short stereoscopic videos. We validate it on both controlled scenes and real videos available on the internet, and show how all the factors we take into account, as well as their interactions, affect viewing comfort. Last, we propose various applications that can benefit from our comfort measurements and metric.

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Section: Stereoscopic Retargetingmentioning

confidence: 99%

A metric of visual comfort for stereoscopic motion

Masiá

et al. 2013

ACM Trans. Graph.

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“…It has been shown that given the simultaneous multiple views, LFs enable improved image analysis, e.g., stereo reconstruction [20], refocusing [29], saliency detection [23], and scene classification [39].…”

Section: Introductionmentioning

confidence: 99%

Depth Recovery from Light Field Using Focal Stack Symmetry

Lin

Chen

Kang

et al. 2015

2015 IEEE International Conference on Computer Vision (ICCV)

120

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We describe a technique to recover depth from a light field (LF) using two proposed features of the LF focal stack. One feature is the property that non-occluding pixels exhibit symmetry along the focal depth dimension centered at the in-focus slice. The other is a data consistency measure based on analysis-by-synthesis, i.e., the difference between the synthesized focal stack given the hypothesized depth map and that from the LF. These terms are used in an iterative optimization framework to extract scene depth. Experimental results on real Lytro and Raytrix data demonstrate that our technique outperforms state-of-the-art solutions and is significantly more robust to noise and undersampling.

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“…Extending this method to remap full-parallax light field content would introduce artifacts because of the increased number of views. Kim et al [10] extend the approach by proposing a framework for the generation of stereoscopic image pairs with per-pixel control over disparity, based on multi-perspective imaging from light fields. While their method might be extended to multi-view images, the associated optimization problem is too costly to be solved in a run-time setting.…”

Section: Related Workmentioning

confidence: 99%

Real-time adaptive content retargeting for live multi-view capture and light field display

et al. 2015

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The discrete nature of multiprojector light field displays results in aliasing when rendering scene points at depths outside the supported depth of field causing visual discomfort. We propose an efficient on-the-fly content-aware real-time depth retargeting algorithm for live 3D light field video to increase the quality of visual perception on a cluster-driven multiprojector light field display. The proposed algorithm is embedded in an end-to-end real-time system capable of capturing and reconstructing light field from multiple calibrated cameras on a full horizontal parallax light field display. By automatically detecting salient regions of a scene, we solve an optimization to derive a nonlinear operator to fit the whole scene within the comfortable viewing range of the light field display. We evaluate the effectiveness of our approach on synthetic and real world scenes.Keywords On-the-fly depth retargeting · GPU · Multiprojector light field display · Visually enhanced live 3D video · Multi-view capture and display

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Multi-perspective stereoscopy from light fields

Cited by 55 publications

References 35 publications

A metric of visual comfort for stereoscopic motion

A metric of visual comfort for stereoscopic motion

Depth Recovery from Light Field Using Focal Stack Symmetry

Real-time adaptive content retargeting for live multi-view capture and light field display

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