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light field salient object detection:A review and benchmark

Computational Visual Media 2022年第4期8卷 509-534页

作者： Keren Fu Yao Jiang Ge-Peng Ji Tao Zhou Qijun Zhao Deng-Ping Fan College of Computer Science Sichuan Universityand National Key Laboratory of Fundamental Science on Synthetic VisionSichuan UniversityChengdu 610065China School of Computer Science Wuhan UniversityWuhan 430072China PCA Lab School of Computer Science and EngineeringNanjing University of Science and TechnologyNanjing 210094China Computer Vision Lab ETH ZürichZürichSwitzerland

Salient object detection(SOD)is a long-standing research topic in computer vision with increasing interest in the past *** light fields record comprehensive information of natural scenes that benefit SOD in a number of ways,using light field inputs to improve saliency detection over conventional RGB inputs is an emerging *** paper provides the first comprehensive review and a benchmark for light field SOD,which has long been lacking in the saliency ***,we introduce light fields,including theory and data forms,and then review existing studies on light field SOD,covering ten traditional models,seven deep learning-based models,a comparative study,and a brief *** datasets for light field SOD are also ***,we benchmark nine representative light field SOD models together with several cutting-edge RGB-D SOD models on four widely used light field datasets,providing insightful discussions and analyses,including a comparison between light field SOD and RGB-D SOD *** to the inconsistency of current datasets,we further generate complete data and supplement focal stacks,depth maps,and multi-view images for them,making them consistent and *** supplemental data make a universal benchmark ***,light field SOD is a specialised problem,because of its diverse data representations and high dependency on acquisition hardware,so it differs greatly from other saliency detection *** provide nine observations on challenges and future directions,and outline several open *** the materials including models,datasets,benchmarking results,and supplemented light field datasets are publicly available at https://***/kerenfu/LFSOD-Survey.

关键词： light field salient object detection(SOD) deep learning benchmarking

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light field depth estimation:A comprehensive survey from principles to future

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High-Confidence Computing 2024年第1期4卷 92-107页

作者： Tun Wang Hao Sheng Rongshan Chen Da Yang Zhenglong Cui Sizhe Wang Ruixuan Cong Mingyuan Zhao State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and EngineeringBeihang UniversityBeijing 100191China Zhongfa Aviation Institute Beihang UniversityHangzhou 311115China Faculty of Applied Sciences Macao Polytechnic UniversityMacao 999078China State Key Laboratory of Software Development Environment School of Computer Science and EngineeringBeihang UniversityBeijing 100191China

light field(LF)depth estimation is an important research direction in the area of computer vision and computational photography,which aims to infer the depth information of different objects in threedimensional scenes by capturing LF *** this new era of significance,this article introduces a survey of the key concepts,methods,novel applications,and future trends in this *** summarize the LF depth estimation methods,which are usually based on the interaction of radiance from rays in all directions of the LF data,such as epipolar-plane,multi-view geometry,focal stack,and deep *** analyze the many challenges facing each of these approaches,including complex algorithms,large amounts of computation,and speed *** addition,this survey summarizes most of the currently available methods,conducts some comparative experiments,discusses the results,and investigates the novel directions in LF depth estimation.

关键词： light field Depth estimation Deep learning Sub-aperture image Epipolar-plane image

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Real-time per-pixel focusing method for light field rendering

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Computational Visual Media 2021年第3期7卷 319-333页

作者： T.Chlubna T.Milet P.Zemcík Faculty of Information Technology Brno University of Technology61200 BrnoCzech Republic

light field rendering is an image-based rendering method that does not use 3 D models but only images of the scene as input to render new *** field approximation,represented as a set of images,suffers from so-called refocusing artifacts due to different depth values of the pixels in the *** information about depths in the scene,proper focusing of the light field scene is limited to a single focusing *** correct focusing method is addressed in this work and a real-time solution is proposed for focusing of light field scenes,based on statistical analysis of the pixel values contributing to the final *** existing techniques,this method does not need precomputed or acquired depth *** requirements and streaming bandwidth are reduced and real-time rendering is possible even for high resolution light field data,yielding visually satisfactory *** evaluation of the proposed method,implemented on a GPU,is presented in this paper.

关键词： image-based rendering light field plenoptic function computational photography

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Camera array calibration for light field acquisition

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Frontiers of Computer Science 2015年第5期9卷 691-702页

作者： Yichao XU Kazuki MAENO Hajime NAGAHARA Rin-ichiro TANIGUCHI Graduate School of Information Science and Electrical Engineering Kyushu University Fukuoka 819-0395 Japan

light field cameras are becoming popular in com- puter vision and graphics, with many research and commercial applications already having been proposed. Various types of cameras have been developed with the camera array being one of the ways of acquiring a 4D light field image using multiple cameras. Camera calibration is essential, since each application requires the correct projection and ray geometry of the fight field. The calibrated parameters are used in the fight field image rectified from the images captured by multiple cameras. Various camera calibration approaches have been proposed for a single camera, multiple cameras, and a moving camera. However, although these approaches can be applied to calibrating camera arrays, they are not effective in terms of accuracy and computational cost. Moreover, less attention has been paid to camera calibration of a light field camera. In this paper, we propose a calibration method for a camera array and a rectification method for generating a light field image from the captured images. We propose a two-step algorithm consisting of closed form initialization and nonlinear refinement, which extends Zhang＇s well-known method to the camera array. More importantly, we introduce a rigid camera constraint whereby the array of cameras is rigidly aligned in the camera array and utilize this constraint in our calibration. Using this constraint, we obtained much faster and more accurate calibration results in the experiments.

关键词： light field camera array calibration rectification digital refocusing

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Key technologies of light field capture for 3D reconstruction in microscopic scene

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Science China(Information Sciences) 2010年第10期53卷 1917-1930页

作者： WANG Yu, JI XiangYang & DAI QiongHai Broadband Networks & Digital Media Lab of Automation Department, Tsinghua University, Beijing 100084, China 1. Broadband Networks & Digital Media Lab of Automation Department Tsinghua University Beijing 100084 China

light field capture for 3D reconstruction in microscopic scene is a very promising and useful technology, which can be extensively applied to life sciences, medicine, materials science, etc. This paper summarizes the key technologies in the evolution of microscopes for capturing 3D information, including wavefrontreconstruction, holography, fluorescence, tomography and so on. To give in-depth insights into them, detailed analyses and comparisons are provided. Finally, some future potential work in terms of light field capture and its application are discussed at length.

关键词： light field 3D reconstruction microscopy

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light field microscopy in biological imaging

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Journal of Innovative Optical Health Sciences 2023年第1期16卷 79-93页

作者： Chengqiang Yi Lanxin Zhu Dongyu Li Peng Fei School of Optical and Electronic Information-Wuhan National Laboratory for Optoelectronics Huazhong University of Science and Technology Wuhan 430074 P.R.China

light field microscopy(LFM),featured for high threedimensional imaging speed and low pho-totoxicity,has emeged as a technique of choice for instantaneous volumetric *** contrast with other scanning-based three dimensional(3D)imaging approaches,LFM enables to encode 3D spatial information in a snapshot manner,permitting high-speed 3D imaging that is only limited by the frame rate of the *** this review,we first introduce the fundamental theory of LFM and current corresponding advanced ***,we summarize various applica-tions of LFM in biological imaging.

关键词： light field deep learning thre-dimensional microscopy

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MPIN:a macro-pixel integration network for light field super-resolution

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Frontiers of Information Technology & Electronic Engineering 2021年第10期22卷 1299-1310页

作者： Xinya WANG Jiayi MA Wenjing GAO Junjun JIANG Electronic Information School Wuhan UniversityWuhan 430072China School of Computer Science and Technology Harbin Institute of TechnologyHarbin 150001China

Most existing light field(LF)super-resolution(SR)methods either fail to fully use angular information or have an unbalanced performance distribution because they use parts of *** address these issues,we propose a novel integration network based on macro-pixel representation for the LF SR task,named *** the entire LF image simultaneously,we couple the spatial and angular information by rearranging the four-dimensional LF image into a two-dimensional macro-pixel ***,two special convolutions are deployed to extract spatial and angular information,*** fully exploit spatial-angular correlations,the integration resblock is designed to merge the two kinds of information for mutual guidance,allowing our method to be *** the macro-pixel representation,an angular shuffle layer is tailored to improve the spatial resolution of the macro-pixel image,which can effectively avoid *** experiments on both synthetic and real-world LF datasets demonstrate that our method can achieve better performance than the state-of-the-art methods qualitatively and ***,the proposed method has an advantage in preserving the inherent epipolar structures of LF images with a balanced distribution of performance.

关键词： light field Super-resolution Macro-pixel representation

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light field Virtual View Rendering Based on EPI-Representations

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ZTE Communications 2016年第3期14卷 55-59页

作者： SUN Yule YU Lu Department of Information Science & Electronic Engineering Zhejiang University

Image-Based Rendering （IBR） is one powerful approach for generating virtual views. It can provide convincing animations without an explicit geometric representation. In this paper, several implementations of light field rendering are summa- rized from prior arts. Several characteristics, such as the regu- lar pattern in Epipolar Plane Images （EPIs）, of light field are explored with detail under 1D parallel camera arrangement. It is proved that it is quite efficient to synthesize virtual views for Super Multi-View （SMV） application, which is in the third phase of Free- Viewpoint Television （FTV）. In comparison with convolutional stereo matching method, in which the inter- mediate view is synthesized by the two adjacent views, light field rendering makes use of more views supplied to get the high-quality views.

关键词： depth estimate Epipolar Plane Image (EPI) light field viewsynthesis

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Structured-light-field 3D Imaging System With Coaxial Projection

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激光与光电子学进展 2023年第8期60卷 261-267页

作者： Zhang Zhijun Wu Qingyang Jiang Yifan Deng Yifeng College of Big Data and Internet Shenzhen Technology UniversityShenzhen 518118GuangdongChina

This paper presents a novel 3D measurement method for a light field camera(LFC)in which 3D information of object space is encoded by a microlens array(MLA).The light ray corresponding to each pixel of the LFC is *** the matching points from at least two subviews exhibit sub-pixel accuracy,the 3D coordinates can be calculated optimally by intersecting light rays of these points matched through phase ***,the proposed method obtains high-resolved results that exceed the subview resolution due to the virtual continuous phase search ***,we combine the LFC and coaxial projection to solve the 3D data loss caused by shadowing and occlusion *** results verify the feasibility of the proposed method,and the measurement error is about 30μm in a depth range of 60 mm.

关键词： light field 3D imaging microlens array structured light

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An overview of computational photography

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Science China(Information Sciences) 2012年第6期55卷 1229-1248页

作者： SUO JinLi,JI XiangYang & DAI QiongHai Department of Automation,Tsinghua University,Beijing 100084,China 1. Department of Automation Tsinghua University Beijing 100084 China

Computational photography is an emerging multidisciplinary *** the last two decades,it has integrated studies across computer vision,computer graphics,signal processing,applied optics and related *** are exploring new ways to break through the limitations of traditional digital imaging for the benefit of photographers,vision and graphics researchers,and image processing *** to much effort in various associated fields,the large variety of issues related to these new methods of photography are described and discussed extensively in this *** give the reader the full picture of the voluminous literature related to computational photography,this paper briefly reviews the wide range of topics in this new field,covering a number of different aspects,including:(i) the various elements of computational imaging systems and new sampling and reconstruction mechanisms;(ii) the different image properties which benefit from computational photography,*** of field,dynamic range;and(iii) the sampling subspaces of visual scenes in the real *** on this systematic review of the previous and ongoing work in this field,we also discuss some open issues and potential new directions in computational *** paper aims to help the reader get to know this new field,including its history,ultimate goals,hot topics,research methodologies,and future directions,and thus build a foundation for further research and related developments.

关键词： computational photography computational imaging plenoptic function light field

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