本文關(guān)鍵詞：光場(chǎng)深度估計(jì)方法的對(duì)比研究　出處：《模式識(shí)別與人工智能》2016年09期 　論文類(lèi)型：期刊論文

  更多相關(guān)文章： 光場(chǎng) 深度估計(jì) 光照 極平面圖像 重聚焦

【摘要】：為了更有效地利用光場(chǎng)信息實(shí)現(xiàn)場(chǎng)景深度的精確估計(jì),文中回顧并深入探討光場(chǎng)的深度估計(jì)問(wèn)題.通過(guò)闡述光場(chǎng)基本理論,將光場(chǎng)深度估計(jì)歸納為基于極平面圖像、多視角圖像及重聚焦的3種方法.在合成數(shù)據(jù)集上,對(duì)比光照變化對(duì)不同算法性能的影響,并構(gòu)建一個(gè)更全面且具有挑戰(zhàn)性的光場(chǎng)數(shù)據(jù)集.在該數(shù)據(jù)集、光場(chǎng)標(biāo)準(zhǔn)數(shù)據(jù)集及Lytro Dataset上,定性及定量分析不同復(fù)雜場(chǎng)景對(duì)算法性能的影響,進(jìn)一步指出該領(lǐng)域的研究方向.
[Abstract]:In order to use the light field information more effectively to realize the accurate depth estimation of the scene, the depth estimation problem of the light field is reviewed and discussed in this paper, and the basic theory of the light field is expounded. The depth estimation of light field is divided into three methods based on polar plane image, multi-view image and refocusing. The effects of illumination on the performance of different algorithms are compared on the composite dataset. A more comprehensive and challenging light field data set is constructed on the data set, optical field standard data set and Lytro Dataset. The effect of different complex scenes on the performance of the algorithm is analyzed qualitatively and quantitatively, and the research direction in this field is pointed out.
【作者單位】： 合肥工業(yè)大學(xué)計(jì)算機(jī)與信息學(xué)院;
【基金】：國(guó)家自然科學(xué)基金項(xiàng)目(No.61403116,61271121) 中國(guó)博士后基金項(xiàng)目(No.2014M560507) 中央高�；究蒲袠I(yè)務(wù)費(fèi)專(zhuān)項(xiàng)資金資助~~
【分類(lèi)號(hào)】：TP391.41
【正文快照】： Supported by National Natural Science Foundation of China(No.61403116,61271121),China Postdoctoral Science Foundation(No.2014M560507),Fundamental Research Funds for the Central Universities深度感知(Depth Perception)是指人眼對(duì)物體遠(yuǎn)近距離的感覺(jué).人眼的深度，

本文編號(hào)：1433409