Unstructured lumigraph rendering

Buehler, Chris; Bosse, Michael; McMillan, Leonard; Gortler, Steven J.; Cohen, Michael F.

doi:10.1145/383259.383309

Cited by 766 publications

(699 citation statements)

References 20 publications

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“…Regions where many such rays intersect indicate potentially interesting objects. 6 We then look for strong arcs centered on each orbit center, i.e., long arcs that pass close to a large number of camera centers (see [67] for more detail on this process). For the Statue of Liberty, for example (Fig.…”

Section: A Orbits and Panoramasmentioning

confidence: 99%

Scene Reconstruction and Visualization From Community Photo Collections

et al. 2010

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| There are billions of photographs on the Internet, representing an extremely large, rich, and nearly comprehensive visual record of virtually every famous place on Earth. Unfortunately, these massive community photo collections are almost completely unstructured, making it very difficult to use them for applications such as the virtual exploration of our world. Over the past several years, advances in computer vision have made it possible to automatically reconstruct 3-D geometryVincluding camera positions and scene modelsVfrom these large, diverse photo collections. Once the geometry is known, we can recover higher level information from the spatial distribution of photos, such as the most common viewpoints and paths through the scene. This paper reviews recent progress on these challenging computer vision problems, and describes how we can use the recovered structure to turn community photo collections into immersive, interactive 3-D experiences.

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Section: A Orbits and Panoramasmentioning

confidence: 99%

Scene Reconstruction and Visualization From Community Photo Collections

et al. 2010

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“…ω i contains the weights of I v i for each output pixel with n i=1 ω i = 1 based on the camera position [46].…”

Section: Floating Texturesmentioning

confidence: 99%

“…These visibility maps are used as input to the soft visibility shader which can be efficiently implemented in a two-pass fragment shader. Next, a weight map is established by calculating the camera weights per output pixel, based on the Unstructured Lumigraph weighting scheme [46]. The final camera weights for each pixel in the output image are obtained by multiplying the weight map with the visbility map and normalizing the result.…”

Section: Gpu Implementationmentioning

confidence: 99%

Towards Plenoptic Raumzeit Reconstruction

Eisemann

Klose

Magnor

2011

Video Processing and Computational Video

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Abstract. The goal of image-based rendering is to evoke a visceral sense of presense in a scene using only photographs or videos. A huge variety of different approaches have been developed during the last decade. Examining the underlying models we find three different main categories: view interpolation based on geometry proxies, pure image interpolation techniques and complete scene flow reconstruction. In this paper we present three approaches for free-viewpoint video, one for each of these categories and discuss their individual benefits and drawbacks. We hope that studying the different approaches will help others in making important design decisions when planning a free-viewpoint video system.

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“…They then use VDTM from the three cameras nearest (in view angle) to each geometric primitive. Buehler, et al [2] present a detailed analysis of the issues, such as resolution, angle, etc. involved with selection of VDTM imagery at each pixel.…”

Section: Related Workmentioning

confidence: 99%

“…Our system dynamically creates a geometric proxy in real time and assigns texture to the proxy using a VDTM technique based on that of [2].…”

Section: Related Workmentioning

confidence: 99%

Combining approximate geometry with view-dependent texture mapping - a hybrid approach to 3D video teleconferencing

Kurashima

Yang

Lastra

Proceedings. XV Brazilian Symposium on Computer Graphics and Image Processing

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Abstract. We present a hybrid system using computer vision and graphics methods that effectively combines fast automatic 3D model extraction with view-dependent texture mapping for the purpose of real-time person-toperson 3D video teleconferencing. In our approach the problem of creating a dense disparity map is bypassed. We compute only a sparse geometric model, which is textured from multiple cameras using an image-based rendering approach. Using a commodity graphics card and three personal computers arranged in a cluster, we achieve a performance of 3 to 4 frames per second. We demonstrate the ability to provide a 3D tele-immersive environment with our system.

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Unstructured lumigraph rendering

Cited by 766 publications

References 20 publications

Scene Reconstruction and Visualization From Community Photo Collections

Scene Reconstruction and Visualization From Community Photo Collections

Towards Plenoptic Raumzeit Reconstruction

Combining approximate geometry with view-dependent texture mapping - a hybrid approach to 3D video teleconferencing

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