Unsupervised extraction of coherent regions for image based rendering

Berent, Jesse; Dragotti, Pier Luigi

doi:10.5244/c.21.28

Cited by 9 publications

(3 citation statements)

References 24 publications

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“…two or more). Note that the constraints applied to the energy minimization are the same as in [10], [13]. However, instead of relying on active contours and the level-set method, we use a patch-based algorithm to find potential layer boundaries.…”

Section: Light Field Structure and Samplingmentioning

confidence: 99%

Adaptive layer extraction for image based rendering

Berent

Dragotti

Brookes

2009

2009 IEEE International Workshop on Multimedia Signal Processing

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Abstract-Image based rendering is a promising way to produce arbitrary views of a scene using images instead of object models. However, depth variations and occlusions cause blurring in the rendered images. The solution is to use some geometrical information in order to steer the interpolation filters according to the depth. The level of detail of this geometry is often predetermined. In this paper, we present a method for extracting depth layers in the presence of occlusions for image based rendering. Moreover, we show how the layer extraction can be made to estimate depth layers in an adaptive manner, based on the spectral analysis of the plenoptic function. The rendering system therefore automatically adapts the number of depth layers based on the scene and the spacing of the sample cameras.

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Section: Light Field Structure and Samplingmentioning

confidence: 99%

Adaptive layer extraction for image based rendering

Berent

Dragotti

Brookes

2009

2009 IEEE International Workshop on Multimedia Signal Processing

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“…Segmentation is a specific research focus in light field editing. Berent and Dragotti [ 67 ] proposed an algorithm to extract coherent regions based on a level set method [ 68 ]. Wanner et al [ 69 ] carried out globally consistent multilabel assignment for light field segmentation.…”

Section: Introductionmentioning

confidence: 99%

Review of light field technologies

Zhou

Zhu

Shi

et al. 2021

Vis. Comput. Ind. Biomed. Art

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Light fields are vector functions that map the geometry of light rays to the corresponding plenoptic attributes. They describe the holographic information of scenes by representing the amount of light flowing in every direction through every point in space. The physical concept of light fields was first proposed in 1936, and light fields are becoming increasingly important in the field of computer graphics, especially with the fast growth of computing capacity as well as network bandwidth. In this article, light field imaging is reviewed from the following aspects with an emphasis on the achievements of the past five years: (1) depth estimation, (2) content editing, (3) image quality, (4) scene reconstruction and view synthesis, and (5) industrial products because the technologies of lights fields also intersect with industrial applications. State-of-the-art research has focused on light field acquisition, manipulation, and display. In addition, the research has extended from the laboratory to industry. According to these achievements and challenges, in the near future, the applications of light fields could offer more portability, accessibility, compatibility, and ability to visualize the world.

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“…This can be done using level sets [29]- [31], but this assumes each segmented object to be fronto-planar to the camera. An alternative is to segment each ray using the spatial and angular neighbourhood.…”

Section: Introductionmentioning

confidence: 99%

Superrays for Efficient Light Field Processing

Hog

Sabater

Guillemot

2017

IEEE J. Sel. Top. Signal Process.

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Abstract-Light field acquisition devices allow capturing scenes with unmatched post-processing possibilities. However, the huge amount of high dimensional data poses challenging problems to light field processing in interactive time. In order to enable light field processing with a tractable complexity, in this paper, we address the problem of light field over-segmentation. We introduce the concept of super-ray, which is a grouping of rays within and across views, as a key component of a light field processing pipeline. The proposed approach is simple, fast, accurate, easily parallelisable, and does not need a dense depth estimation. We demonstrate experimentally the efficiency of the proposed approach on real and synthetic datasets, for sparsely and densely sampled light fields. As super-rays capture a coarse scene geometry information, we also present how they can be used for real time light field segmentation and correcting refocusing angular aliasing.

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Unsupervised extraction of coherent regions for image based rendering

Cited by 9 publications

References 24 publications

Adaptive layer extraction for image based rendering

Adaptive layer extraction for image based rendering

Review of light field technologies

Superrays for Efficient Light Field Processing

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