Light Field Sampling
暫譯: 光場取樣
Zhang/Chen
- 出版商: Morgan & Claypool
- 出版日期: 2006-08-31
- 售價: $1,930
- 貴賓價: 9.5 折 $1,834
- 語言: 英文
- 頁數: 102
- ISBN: 1598293907
- ISBN-13: 9781598293906
海外代購書籍(需單獨結帳)
商品描述
Description
Light field is one of the most representative image-based rendering techniques that generate novel virtual views from images instead of 3D models. The light field capture and rendering process can be considered as a procedure of sampling the light rays in the space and interpolating those in novel views. As a result, light field can be studied as a high-dimensional signal sampling problem, which has attracted a lot of research interest and become a convergence point between computer graphics and signal processing, and even computer vision.
This lecture focuses on answering two questions regarding light field sampling, namely how many images are needed for a light field, and if such number is limited, where we should capture them. The book can be divided into three parts.
First, we give a complete analysis on uniform sampling of IBR data. By introducing the surface plenoptic function, we are able to analyze the Fourier spectrum of non-Lambertian and occluded scenes. Given the spectrum, we also apply the generalized sampling theorem on the IBR data, which results in better rendering quality than rectangular sampling for complex scenes. Such uniform sampling analysis provides general guidelines on how the images in IBR should be taken. For instance, it shows that non-Lambertian and occluded scenes often require a higher sampling rate.
Next, we describe a very general sampling framework named freeform sampling. Freeform sampling handles three kinds of problems: sample reduction, minimum sampling rate to meet an error requirement, and minimization of reconstruction error given a fixed number of samples. When the to-be-reconstructed function values are unknown, freeform sampling becomes active sampling. Algorithms of active sampling are developed for light field and show better results than the traditional uniform sampling approach.
Third, we present a self-reconfigurable camera array that we developed, which features a very efficient algorithm for real-time rendering and the ability of automatically reconfiguring the cameras to improve the rendering quality. Both are based on active sampling. Our camera array is able to render dynamic scenes interactively at high quality. To the best of our knowledge, it is the first camera array that can reconfigure the camera positions automatically.
商品描述(中文翻譯)
**描述**
光場是最具代表性的影像基礎渲染技術之一,它從影像生成新穎的虛擬視圖,而不是從3D模型生成。光場的捕捉和渲染過程可以視為在空間中對光線進行取樣並在新視圖中進行插值的過程。因此,光場可以被研究為一個高維信號取樣問題,這引起了大量的研究興趣,並成為計算機圖形學、信號處理,甚至計算機視覺之間的交匯點。
本講座專注於回答有關光場取樣的兩個問題,即一個光場需要多少影像,以及如果這個數量是有限的,我們應該在哪裡捕捉它們。本書可以分為三個部分。
首先,我們對IBR數據的均勻取樣進行了完整的分析。通過引入表面全光函數,我們能夠分析非朗伯和遮擋場景的傅立葉頻譜。根據頻譜,我們還將廣義取樣定理應用於IBR數據,這使得在複雜場景中獲得比矩形取樣更好的渲染質量。這種均勻取樣分析提供了有關如何拍攝IBR影像的一般指導。例如,它顯示非朗伯和遮擋場景通常需要更高的取樣率。
接下來,我們描述了一個非常通用的取樣框架,稱為自由形狀取樣。自由形狀取樣處理三種問題:樣本減少、滿足誤差要求的最小取樣率,以及在固定樣本數下最小化重建誤差。當待重建的函數值未知時,自由形狀取樣變為主動取樣。針對光場開發的主動取樣算法顯示出比傳統均勻取樣方法更好的結果。
第三,我們介紹了一個自我重構的相機陣列,該陣列具有非常高效的實時渲染算法和自動重構相機以提高渲染質量的能力。這兩者都基於主動取樣。我們的相機陣列能夠以高質量互動渲染動態場景。據我們所知,這是第一個能夠自動重構相機位置的相機陣列。