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| 1 | Global fusion of generalized camera model for efficient large-scale structure from motion显示文摘Recently,interest has grown in building large-scale3D city models[1]from images captured by multicamera systems,such as cameras mounted on a car,e.g.,Google Street View,or on an unmanned aerial vehicle,e.g.,oblique airborne photogrammetry.From such images。 | Hainan CUI Shuhan SHEN Zhanyi HU | 2017 | Science China(Information Sciences)2017，60，3： | 3 |
| 2 | Geographic,Geometrical and Semantic Reconstruction of Urban Scene from High Resolution Oblique Aerial Images显示文摘An effective approach is proposed for 3D urban scene reconstruction in the form of point cloud with semantic labeling. Starting from high resolution oblique aerial images,our approach proceeds through three main stages: geographic reconstruction, geometrical reconstruction and semantic reconstruction. The absolute position and orientation of all the cameras relative to the real world are recovered in the geographic reconstruction stage. Then, in the geometrical reconstruction stage,an improved multi-view stereo matching method is employed to produce 3D dense points with color and normal information by taking into account the prior knowledge of aerial imagery.Finally the point cloud is classified into three classes(building,vegetation, and ground) by a rule-based hierarchical approach in the semantic reconstruction step. Experiments on complex urban scene show that our proposed 3-stage approach could generate reasonable reconstruction result robustly and efficiently.By comparing our final semantic reconstruction result with the manually labeled ground truth, classification accuracies from86.75% to 93.02% are obtained. | Xiaofeng Sun Shuhan Shen Hainan Cui Lihua Hu Zhanyi Hu | 2019 | IEEE/CAA Journal of Automatica Sinica2019，6，1： | 2 |
| 3 | Multi-source data-based 3D digital preservation of large scale ancient chinese architecture:A case report显示文摘The 3D digitalization and documentation of ancient Chinese architecture is challenging because of architectural complexity and structural delicacy.To generate complete and detailed models of this architecture,it is better to acquire,process,and fuse multi-source data instead of single-source data.In this paper,we describe our work on 3D digital preservation of ancient Chinese architecture based on multi source data.We first briefly introduce two surveyed ancient Chinese temples,Foguang Temple and Nanchan Temple.Then,we report the data acquisition equipment we used and the multi-source data we acquired.Finally,we provide an overview of several applications we conducted based on the acquired data,including ground and aerial image fusion,image and LiDAR(light detection and ranging)data fusion,and architectural scene surface reconstruction and semantic modeling.We believe that it is necessary to involve multi-source data for the 3D digital preservation of ancient Chinese architecture,and that the work in this paper will serve as a heuristic guideline for the related research communities. | Xiang GAO Hainan CUI Lingjie ZHU Tianxin SHI Shuhan SHEN | 2019 | Virtual Reality & Intelligent Hardware2019，1，5： | 1 |
| 4 | Learning stratified 3D reconstruction显示文摘Stratified 3 D reconstruction, or a layer-by-layer 3 D reconstruction upgraded from projective to affine, then to the final metric reconstruction, is a well-known 3 D reconstruction method in computer vision. It is also a key supporting technology for various well-known applications, such as streetview, smart3 D, oblique photogrammetry. Generally speaking, the existing computer vision methods in the literature can be roughly classified into either the geometry-based approaches for spatial vision or the learning-based approaches for object vision. Although deep learning has demonstrated tremendous success in object vision in recent years,learning 3 D scene reconstruction from multiple images is still rare, even not existent, except for those on depth learning from single images. This study is to explore the feasibility of learning the stratified 3 D reconstruction from putative point correspondences across images, and to assess whether it could also be as robust to matching outliers as the traditional geometry-based methods do. In this study, a special parsimonious neural network is designed for the learning. Our results show that it is indeed possible to learn a stratified 3 D reconstruction from noisy image point correspondences, and the learnt reconstruction results appear satisfactory although they are still not on a par with the state-of-the-arts in the structurefrom-motion community due to largely its lack of an explicit robust outlier detector such as random sample consensus(RANSAC). To the best of our knowledge, our study is the first attempt in the literature to learn3 D scene reconstruction from multiple images. Our results also show that how to implicitly or explicitly integrate an outlier detector in learning methods is a key problem to solve in order to learn comparable3 D scene structures to those by the current geometry-based state-of-the-arts. Otherwise any significant advancement of learning 3 D structures from multiple images seems difficult, if not impossible. Besides, we even speculate that deep learning might be, in nature, not suitable for learning 3 D structure from multiple images, or more generally, for solving spatial vision problems. | Qiulei DONG Mao SHU Hainan CUI Huarong XU Zhanyi HU | 2018 | Science China(Information Sciences)2018，61，2： | 1 |
| 5 | Programmable deaminase-free base editors for G-to-Y conversion by engineered glycosylase显示文摘Current DNA base editors contain nuclease and DNA deaminase that enables deamination of cytosine(C)or adenine(A),but no method for guanine(G)or thymine(T)editing is available at present.Here we developed a deaminase-free glycosylase-based guanine base editor(gGBE)with G editing ability,by fusing Cas9 nickase with engineered N-methylpurine DNA glycosylase protein(MPG).By several rounds of MPG mutagenesis via unbiased and rational screening using an intron-split EGFP reporter,we demonstrated that gGBE with engineered MPG could increase G editing efficiency by more than 1500 fold.Furthermore,this gGBE exhibited high base editing efficiency(up to 81.2%)and high G-to-T or G-to-C(i.e.G-to-Y)conversion ratio(up to 0.95)in both cultured human cells and mouse embryos.Thus,we have provided a proof-of-concept of a new base editing approach by endowing the engineered DNA glycosylase the capability to selectively excise a new type of substrate. | Huawei Tong Nana Liu Yinghui Wei Yingsi Zhou Yun Li Danni Wu Ming Jin Shuna Cui Hengbin Li Guoling Li Jingxing Zhou Yuan Yuan Hainan Zhang Linyu Shi Xuan Yao Hui Yang | 2023 | National Science Review2023，10，8： | 1 |
| 6 | Application of graphene for preconcentration and highly sensitive stripping voltammetric analysis of organophosphate pesticide显示文摘 | Shuo Wu Xiaoqin Lan Lijun Cui Lihui Zhang Shengyang Tao Hainan Wang Mei Han Zhiguang Liu Changgong Meng | 2011 | Analytica Chimica Acta2011，，2： | 1 |
| 7 | Effective two-view line segment reconstruction based on structure priors显示文摘Dear editor,For the 3D reconstruction of the line segments detected in images,traditional line segment(LS)detection and matching methods[1,2]usually encounter the following problems when noise and illumination variation are involved:(1)the detected LSs deviate from real scene structures;(2)only a minority of the detected LSs with better discriminating features can be correctly matched(see Figure 1(a));(3)a certain amount of falsely matched LSs are generated.As a result,as shown in Figure 1(e)and(f),the 3D LSs recons true ted from the LS matches contain larger errors,and are also too sparse to describe the complete scene structures. | Wei WANG Hainan CUI Wei GAO Zhanyi HU | 2020 | Science China(Information Sciences)2020，63，1： | 0 |
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