On the number of samples needed in light field rendering with constant-depth assumption

Lin, Zhouchen; Shum, Heung-Yeung

doi:10.1109/cvpr.2000.855873

Cited by 16 publications

(1 citation statement)

References 9 publications

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“…The capture of densely sampled views in the real world is a very challenging task, frustrating the experience with 3D light field displays. A way to get around this problem is to employ view interpolation techniques to synthesize (render) dense virtual views for 3D light field display [23][24][25][26][27].…”

Section: Light Field Visualizationmentioning

confidence: 99%

Learning-based light field imaging: an overview

Mahmoudpour,

Pagliari,

Schelkens

2024

J Image Video Proc.

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Conventional photography can only provide a two-dimensional image of the scene, whereas emerging imaging modalities such as light field enable the representation of higher dimensional visual information by capturing light rays from different directions. Light fields provide immersive experiences, a sense of presence in the scene, and can enhance different vision tasks. Hence, research into light field processing methods has become increasingly popular. It does, however, come at the cost of higher data volume and computational complexity. With the growing deployment of machine-learning and deep architectures in image processing applications, a paradigm shift toward learning-based approaches has also been observed in the design of light field processing methods. Various learning-based approaches are developed to process the high volume of light field data efficiently for different vision tasks while improving performance. Taking into account the diversity of light field vision tasks and the deployed learning-based frameworks, it is necessary to survey the scattered learning-based works in the domain to gain insight into the current trends and challenges. This paper aims to review the existing learning-based solutions for light field imaging and to summarize the most promising frameworks. Moreover, evaluation methods and available light field datasets are highlighted. Lastly, the review concludes with a brief outlook for future research directions.

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