Automatic 3D reconstruction of structured indoor environments

Creating high-level structured 3D models of real-world indoor scenes from captured data is a fundamental task which has important applications in many fields. Given the complexity and variability of interior environments and the need to cope with noisy and partial captured data, many open research problems remain, despite the substantial progress made in the past decade. In this tutorial, we provide an up-to-date integrative view of the field, bridging complementary views coming from computer graphics and computer vision. After providing a characterization of input sources, we define the structure of output models and the priors exploited to bridge the gap between imperfect sources and desired output. We then identify and discuss the main components of a structured reconstruction pipeline, and review how they are combined in scalable solutions working at the building level. We finally point out relevant research issues and analyze research trends.

[1]  Enrico Gobbetti,et al.  State‐of‐the‐art in Automatic 3D Reconstruction of Structured Indoor Environments , 2020, Comput. Graph. Forum.

[2]  Silvio Savarese,et al.  3D Scene Graph: A Structure for Unified Semantics, 3D Space, and Camera , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).

[3]  Alberto Jaspe Villanueva,et al.  Automatic modeling of cluttered multi‐room floor plans from panoramic images , 2019, Comput. Graph. Forum.

[4]  Haihong Zhu,et al.  Automatic Indoor Reconstruction from Point Clouds in Multi-room Environments with Curved Walls , 2019, Sensors.

[5]  Jiacheng Chen,et al.  Floor-SP: Inverse CAD for Floorplans by Sequential Room-Wise Shortest Path , 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).

[6]  Zihan Zhou,et al.  Structured3D: A Large Photo-realistic Dataset for Structured 3D Modeling , 2019, ECCV.

[7]  Hao Wu,et al.  Learning to Reconstruct and Understand Indoor Scenes From Sparse Views , 2019, IEEE Transactions on Image Processing.

[8]  Matthias Nießner,et al.  Active Scene Understanding via Online Semantic Reconstruction , 2019, Comput. Graph. Forum.

[9]  Yang Cui,et al.  Automatic 3-D Reconstruction of Indoor Environment With Mobile Laser Scanning Point Clouds , 2019, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[10]  Reinhard Klein,et al.  Automatic reconstruction of fully volumetric 3D building models from point clouds , 2019, ISPRS Journal of Photogrammetry and Remote Sensing.

[11]  Long Quan,et al.  Recurrent MVSNet for High-Resolution Multi-View Stereo Depth Inference , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[12]  Cheng Sun,et al.  HorizonNet: Learning Room Layout With 1D Representation and Pano Stretch Data Augmentation , 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[13]  Yan Zhou,et al.  Low-Cost and Efficient Indoor 3D Reconstruction through Annotated Hierarchical Structure-from-Motion , 2018, Remote. Sens..

[14]  Wolfgang Reif,et al.  Multipotent Systems: Combining Planning, Self-Organization, and Reconfiguration in Modular Robot Ensembles , 2018, Sensors.

[15]  Matthias Nießner,et al.  3D-SIS: 3D Semantic Instance Segmentation of RGB-D Scans , 2018, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[16]  Jan Kautz,et al.  PlaneRCNN: 3D Plane Detection and Reconstruction From a Single Image , 2018, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[17]  Roberto Scopigno,et al.  Recovering 3D existing-conditions of indoor structures from spherical images , 2018, Comput. Graph..

[18]  Peter Wonka,et al.  DuLa-Net: A Dual-Projection Network for Estimating Room Layouts From a Single RGB Panorama , 2018, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[19]  Roberto Scopigno,et al.  3D floor plan recovery from overlapping spherical images , 2018, Computational Visual Media.

[20]  Zihan Zhou,et al.  Recovering 3D Planes from a Single Image via Convolutional Neural Networks , 2018, ECCV.

[21]  Tamy Boubekeur,et al.  A Survey of Simple Geometric Primitives Detection Methods for Captured 3D Data , 2018, Comput. Graph. Forum.

[22]  Shi Jin,et al.  Automatic 3D Indoor Scene Modeling from Single Panorama , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.

[23]  Matthias Nießner,et al.  State of the Art on 3D Reconstruction with RGB‐D Cameras , 2018, Comput. Graph. Forum.

[24]  Jörg Stückler,et al.  The TUM VI Benchmark for Evaluating Visual-Inertial Odometry , 2018, 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

[25]  Jimei Yang,et al.  PlaneNet: Piece-Wise Planar Reconstruction from a Single RGB Image , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.

[26]  Yasutaka Furukawa,et al.  FloorNet: A Unified Framework for Floorplan Reconstruction from 3D Scans , 2018, ECCV.

[27]  Derek Hoiem,et al.  LayoutNet: Reconstructing the 3D Room Layout from a Single RGB Image , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.

[28]  Juha Hyyppä,et al.  Automated large scale indoor reconstruction using vehicle survey data , 2018, 2018 Ubiquitous Positioning, Indoor Navigation and Location-Based Services (UPINLBS).

[29]  Bo Yang,et al.  Dense 3D Object Reconstruction from a Single Depth View , 2018, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[30]  Matthias Nießner,et al.  ScanComplete: Large-Scale Scene Completion and Semantic Segmentation for 3D Scans , 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.

[31]  E. Gobbetti,et al.  Mobile graphics , 2017, SIGGRAPH ASIA.

[32]  Bin Zhou,et al.  Adaptive synthesis of indoor scenes via activity-associated object relation graphs , 2017, ACM Trans. Graph..

[33]  Leonidas J. Guibas,et al.  3Dlite , 2017, ACM Trans. Graph..

[34]  Andrea Fusiello,et al.  Practical and Efficient Multi-view Matching , 2017, 2017 IEEE International Conference on Computer Vision (ICCV).

[35]  Jiajun Wu,et al.  Raster-to-Vector: Revisiting Floorplan Transformation , 2017, 2017 IEEE International Conference on Computer Vision (ICCV).

[36]  Matthias Nießner,et al.  Matterport3D: Learning from RGB-D Data in Indoor Environments , 2017, 2017 International Conference on 3D Vision (3DV).

[37]  Marc Pollefeys,et al.  Indoor Scan2BIM: Building information models of house interiors , 2017, 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

[38]  A. Markham,et al.  3D Object Reconstruction from a Single Depth View with Adversarial Learning , 2017, 2017 IEEE International Conference on Computer Vision Workshops (ICCVW).

[39]  Juha Hyyppä,et al.  Comparison of the Selected State-Of-The-Art 3D Indoor Scanning and Point Cloud Generation Methods , 2017, Remote. Sens..

[40]  Renato Pajarola,et al.  Exploiting the room structure of buildings for scalable architectural modeling of interiors , 2017, SIGGRAPH Posters.

[41]  Torsten Sattler,et al.  A Multi-view Stereo Benchmark with High-Resolution Images and Multi-camera Videos , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[42]  Richard Szeliski,et al.  Low-cost 360 stereo photography and video capture , 2017, ACM Trans. Graph..

[43]  Eckehard G. Steinbach,et al.  Room segmentation in 3D point clouds using anisotropic potential fields , 2017, 2017 IEEE International Conference on Multimedia and Expo (ICME).

[44]  Jitendra Malik,et al.  Learning Category-Specific Deformable 3D Models for Object Reconstruction , 2017, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[45]  Ross B. Girshick,et al.  Mask R-CNN , 2017, 1703.06870.

[46]  Yanwen Guo,et al.  A Data-Driven Approach for Furniture and Indoor Scene Colorization , 2017, IEEE Transactions on Visualization and Computer Graphics.

[47]  Matthias Nießner,et al.  ScanNet: Richly-Annotated 3D Reconstructions of Indoor Scenes , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[48]  Silvio Savarese,et al.  Joint 2D-3D-Semantic Data for Indoor Scene Understanding , 2017, ArXiv.

[49]  Axel Wendt,et al.  Automatic Room Segmentation From Unstructured 3-D Data of Indoor Environments , 2017, IEEE Robotics and Automation Letters.

[50]  Pierre Alliez,et al.  A Survey of Surface Reconstruction from Point Clouds , 2017, Comput. Graph. Forum.

[51]  Ali Farhadi,et al.  YOLO9000: Better, Faster, Stronger , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[52]  Thomas A. Funkhouser,et al.  Semantic Scene Completion from a Single Depth Image , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[53]  Roberto Scopigno,et al.  Mobile reconstruction and exploration of indoor structures exploiting omnidirectional images , 2016, SIGGRAPH ASIA Mobile Graphics and Interactive Applications.

[54]  Daniel Cremers,et al.  Image-Based Localization Using LSTMs for Structured Feature Correlation , 2016, 2017 IEEE International Conference on Computer Vision (ICCV).

[55]  Michael F. Cohen,et al.  Emptying, refurnishing, and relighting indoor spaces , 2016, ACM Trans. Graph..

[56]  Roberto Scopigno,et al.  Mobile Mapping and Visualization of Indoor Structures to Simplify Scene Understanding and Location Awareness , 2016, ECCV Workshops.

[57]  Duc Thanh Nguyen,et al.  SceneNN: A Scene Meshes Dataset with aNNotations , 2016, 2016 Fourth International Conference on 3D Vision (3DV).

[58]  Björn Stenger,et al.  Pano2CAD: Room Layout from a Single Panorama Image , 2016, 2017 IEEE Winter Conference on Applications of Computer Vision (WACV).

[59]  Q. Tian,et al.  SIFT Meets CNN: A Decade Survey of Instance Retrieval , 2016, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[60]  Matthias Nießner,et al.  PiGraphs , 2016, ACM Trans. Graph..

[61]  Silvio Savarese,et al.  3D Semantic Parsing of Large-Scale Indoor Spaces , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[62]  Hui Zhang,et al.  Efficient 3D Room Shape Recovery from a Single Panorama , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[63]  H. Zhang,et al.  Learning 3D Scene Synthesis from Annotated RGB‐D Images , 2016, Comput. Graph. Forum.

[64]  Simon J. Julier,et al.  Structured Prediction of Unobserved Voxels from a Single Depth Image , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[65]  Matthias Nießner,et al.  BundleFusion , 2016, TOGS.

[66]  Michael Firman RGBD Datasets: Past, Present and Future , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).

[67]  Enrico Gobbetti,et al.  Omnidirectional image capture on mobile devices for fast automatic generation of 2.5D indoor maps , 2016, 2016 IEEE Winter Conference on Applications of Computer Vision (WACV).

[68]  Reinhard Klein,et al.  Automatic reconstruction of parametric building models from indoor point clouds , 2016, Comput. Graph..

[69]  Y. Bastanlar,et al.  A direct approach for object detection with catadioptric omnidirectional cameras , 2016, Signal Image Video Process..

[70]  Sven Oesau,et al.  Planar Shape Detection and Regularization in Tandem , 2016, Comput. Graph. Forum.

[71]  Radomír Mech,et al.  Minimum Barrier Salient Object Detection at 80 FPS , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).

[72]  Hang Yang,et al.  Structured Indoor Modeling , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).

[73]  Shi-Min Hu,et al.  3D indoor scene modeling from RGB-D data: a survey , 2015, Computational Visual Media.

[74]  Kun Zhou,et al.  Online Structure Analysis for Real-Time Indoor Scene Reconstruction , 2015, ACM Trans. Graph..

[75]  Wei Sun,et al.  Autoscanning for coupled scene reconstruction and proactive object analysis , 2015, ACM Trans. Graph..

[76]  Matthias Nießner,et al.  Activity-centric scene synthesis for functional 3D scene modeling , 2015, ACM Trans. Graph..

[77]  Shi-Min Hu,et al.  Magic decorator , 2015, ACM Trans. Graph..

[78]  Reinhard Klein,et al.  Automatic generation of structural building descriptions from 3D point cloud scans , 2015, 2014 International Conference on Computer Graphics Theory and Applications (GRAPP).

[79]  Avideh Zakhor,et al.  Floor plan generation and room labeling of indoor environments from laser range data , 2015, 2014 International Conference on Computer Graphics Theory and Applications (GRAPP).

[80]  Niloy J. Mitra,et al.  RAPter , 2015, ACM Trans. Graph..

[81]  Vladlen Koltun,et al.  Robust reconstruction of indoor scenes , 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[82]  Leonidas J. Guibas,et al.  Render for CNN: Viewpoint Estimation in Images Using CNNs Trained with Rendered 3D Model Views , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).

[83]  Leonidas J. Guibas,et al.  Database‐Assisted Object Retrieval for Real‐Time 3D Reconstruction , 2015, Comput. Graph. Forum.

[84]  Manolis I. A. Lourakis,et al.  Automated as-built 3D reconstruction of civil infrastructure using computer vision: Achievements, opportunities, and challenges , 2015, Adv. Eng. Informatics.

[85]  Avideh Zakhor,et al.  Fast, Automated, Scalable Generation of Textured 3D Models of Indoor Environments , 2015, IEEE Journal of Selected Topics in Signal Processing.

[86]  Carl T. Haas,et al.  State of research in automatic as-built modelling , 2015, Adv. Eng. Informatics.

[87]  Enrico Gobbetti,et al.  Interactive Mapping of Indoor Building Structures through Mobile Devices , 2014, 2014 2nd International Conference on 3D Vision.

[88]  Kang Chen,et al.  Automatic semantic modeling of indoor scenes from low-quality RGB-D data using contextual information , 2014, ACM Trans. Graph..

[89]  Renato Pajarola,et al.  Automatic room detection and reconstruction in cluttered indoor environments with complex room layouts , 2014, Comput. Graph..

[90]  A. Davison,et al.  A benchmark for RGB-D visual odometry, 3D reconstruction and SLAM , 2014, 2014 IEEE International Conference on Robotics and Automation (ICRA).

[91]  Dieter Fox,et al.  Unsupervised feature learning for 3D scene labeling , 2014, 2014 IEEE International Conference on Robotics and Automation (ICRA).

[92]  Yinda Zhang,et al.  PanoContext: A Whole-Room 3D Context Model for Panoramic Scene Understanding , 2014, ECCV.

[93]  Martial Hebert,et al.  3DNN: 3D Nearest Neighbor , 2014, International Journal of Computer Vision.

[94]  András Bódis-Szomorú,et al.  Fast, Approximate Piecewise-Planar Modeling Based on Sparse Structure-from-Motion and Superpixels , 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.

[95]  Ricardo Cabral,et al.  Piecewise Planar and Compact Floorplan Reconstruction from Images , 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.

[96]  Roberto Scopigno,et al.  ExploreMaps: Efficient construction and ubiquitous exploration of panoramic view graphs of complex 3D environments , 2014, Comput. Graph. Forum.

[97]  Olga Sorkine-Hornung,et al.  Object detection and classification from large‐scale cluttered indoor scans , 2014, Comput. Graph. Forum.

[98]  Renato Pajarola,et al.  Reconstructing Complex Indoor Environments with Arbitrary Wall Orientations , 2014, Eurographics.

[99]  Sven Oesau,et al.  Indoor scene reconstruction using feature sensitive primitive extraction and graph-cut , 2014 .

[100]  Silvio Savarese,et al.  Beyond PASCAL: A benchmark for 3D object detection in the wild , 2014, IEEE Winter Conference on Applications of Computer Vision.

[101]  Silvio Savarese,et al.  Understanding the 3D layout of a cluttered room from multiple images , 2014, IEEE Winter Conference on Applications of Computer Vision.

[102]  Frank Schultmann,et al.  Building Information Modeling (BIM) for existing buildings — Literature review and future needs , 2014 .

[103]  Li Li,et al.  Feature-based attention is independent of object appearance. , 2014, Journal of vision.

[104]  Adnan Ahmed Khan,et al.  Selection of VoIP CODECs for Different Networks based on QoS Analysis , 2013 .

[105]  Jian Zhang,et al.  Estimating the 3D Layout of Indoor Scenes and Its Clutter from Depth Sensors , 2013, 2013 IEEE International Conference on Computer Vision.

[106]  Andrew Owens,et al.  SUN3D: A Database of Big Spaces Reconstructed Using SfM and Object Labels , 2013, 2013 IEEE International Conference on Computer Vision.

[107]  Derek Hoiem,et al.  Support Surface Prediction in Indoor Scenes , 2013, 2013 IEEE International Conference on Computer Vision.

[108]  Sanja Fidler,et al.  Box in the Box: Joint 3D Layout and Object Reasoning from Single Images , 2013, 2013 IEEE International Conference on Computer Vision.

[109]  Daniel G. Aliaga,et al.  A Survey of Urban Reconstruction , 2013, Comput. Graph. Forum.

[110]  Shimin Hu,et al.  Sketch2Scene , 2013, ACM Trans. Graph..

[111]  Y. Lipman,et al.  Semantizing Complex 3D Scenes using Constrained Attribute Grammars , 2013, SGP '13.

[112]  Avideh Zakhor,et al.  Watertight Planar Surface Meshing of Indoor Point-Clouds with Voxel Carving , 2013, 2013 International Conference on 3D Vision.

[113]  Kobus Barnard,et al.  Understanding Bayesian Rooms Using Composite 3D Object Models , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.

[114]  Tsuhan Chen,et al.  3D-Based Reasoning with Blocks, Support, and Stability , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.

[115]  Luc Van Gool,et al.  Bayesian Grammar Learning for Inverse Procedural Modeling , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.

[116]  Thorsten Joachims,et al.  Contextually guided semantic labeling and search for three-dimensional point clouds , 2013, Int. J. Robotics Res..

[117]  Kun Zhou,et al.  An interactive approach to semantic modeling of indoor scenes with an RGBD camera , 2012, ACM Trans. Graph..

[118]  Hojung Cha,et al.  Unsupervised Construction of an Indoor Floor Plan Using a Smartphone , 2012, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

[119]  N. Mitra,et al.  Acquiring 3D indoor environments with variability and repetition , 2012, ACM Trans. Graph..

[120]  Shi-Min Hu,et al.  Structure recovery by part assembly , 2012, ACM Trans. Graph..

[121]  Ke Xie,et al.  A search-classify approach for cluttered indoor scene understanding , 2012, ACM Trans. Graph..

[122]  Steven M. Seitz,et al.  Photo Tours , 2012, 2012 Second International Conference on 3D Imaging, Modeling, Processing, Visualization & Transmission.

[123]  Avideh Zakhor,et al.  Watertight As-Built Architectural Floor Plans Generated from Laser Range Data , 2012, 2012 Second International Conference on 3D Imaging, Modeling, Processing, Visualization & Transmission.

[124]  Jianxiong Xiao,et al.  Reconstructing the World’s Museums , 2012, International Journal of Computer Vision.

[125]  Derek Hoiem,et al.  Indoor Segmentation and Support Inference from RGBD Images , 2012, ECCV.

[126]  Steven M. Seitz,et al.  Capturing indoor scenes with smartphones , 2012, UIST.

[127]  Avideh Zakhor,et al.  Planar 3D modeling of building interiors from point cloud data , 2012, 2012 19th IEEE International Conference on Image Processing.

[128]  Matei Stroila,et al.  Route Visualization in Indoor Panoramic Imagery with Open Area Maps , 2012, 2012 IEEE International Conference on Multimedia and Expo Workshops.

[129]  Eli Shechtman,et al.  Image melding , 2012, ACM Trans. Graph..

[130]  Krista A. Ehinger,et al.  Recognizing scene viewpoint using panoramic place representation , 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.

[131]  Daniel Fried,et al.  Bayesian geometric modeling of indoor scenes , 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.

[132]  David A. Forsyth,et al.  Recovering free space of indoor scenes from a single image , 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.

[133]  Mohamed Aly,et al.  Street view goes indoors: Automatic pose estimation from uncalibrated unordered spherical panoramas , 2012, 2012 IEEE Workshop on the Applications of Computer Vision (WACV).

[134]  Hyun-Ki Hong,et al.  People detection method using graphics processing units for a mobile robot with an omnidirectional camera , 2011 .

[135]  Ian D. Reid,et al.  Manhattan scene understanding using monocular, stereo, and 3D features , 2011, 2011 International Conference on Computer Vision.

[136]  Changhai Xu,et al.  Real-time indoor scene understanding using Bayesian filtering with motion cues , 2011, 2011 International Conference on Computer Vision.

[137]  Andrew W. Fitzgibbon,et al.  KinectFusion: real-time 3D reconstruction and interaction using a moving depth camera , 2011, UIST.

[138]  Maneesh Agrawala,et al.  Interactive furniture layout using interior design guidelines , 2011, ACM Trans. Graph..

[139]  Burcu Akinci,et al.  Automatic Creation of Semantically Rich 3D Building Models from Laser Scanner Data , 2011 .

[140]  Alexei A. Efros,et al.  From 3D scene geometry to human workspace , 2011, CVPR 2011.

[141]  Antonio Adán,et al.  3D Reconstruction of Interior Wall Surfaces under Occlusion and Clutter , 2011, 2011 International Conference on 3D Imaging, Modeling, Processing, Visualization and Transmission.

[142]  Takeo Kanade,et al.  Estimating Spatial Layout of Rooms using Volumetric Reasoning about Objects and Surfaces , 2010, NIPS.

[143]  Burcu Akinci,et al.  Automatic Reconstruction of As-Built Building Information Models from Laser-Scanned Point Clouds: A Review of Related Techniques | NIST , 2010 .

[144]  Yohan Dupuis,et al.  Fusion of Omnidirectional and PTZ Cameras for Face Detection and Tracking , 2010, 2010 International Conference on Emerging Security Technologies.

[145]  Stephen Gould,et al.  Discriminative learning with latent variables for cluttered indoor scene understanding , 2010, CACM.

[146]  David A. Forsyth,et al.  Thinking Inside the Box: Using Appearance Models and Context Based on Room Geometry , 2010, ECCV.

[147]  Ian D. Reid,et al.  A Dynamic Programming Approach to Reconstructing Building Interiors , 2010, ECCV.

[148]  Jan-Michael Frahm,et al.  Piecewise planar and non-planar stereo for urban scene reconstruction , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[149]  Jean-Philippe Pons,et al.  Robust piecewise-planar 3D reconstruction and completion from large-scale unstructured point data , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[150]  Roland Siegwart,et al.  MAV navigation through indoor corridors using optical flow , 2010, 2010 IEEE International Conference on Robotics and Automation.

[151]  Jan Boehm,et al.  Automated 3D Reconstruction of Interiors from Point Clouds , 2010 .

[152]  Mani Golparvar-Fard,et al.  Visualization of construction progress monitoring with 4D simulation model overlaid on time-lapsed photographs , 2009 .

[153]  Ming-Liang Wang,et al.  Object recognition from omnidirectional visual sensing for mobile robot applications , 2009, 2009 IEEE International Conference on Systems, Man and Cybernetics.

[154]  Derek Hoiem,et al.  Recovering the spatial layout of cluttered rooms , 2009, 2009 IEEE 12th International Conference on Computer Vision.

[155]  Richard Szeliski,et al.  Piecewise planar stereo for image-based rendering , 2009, 2009 IEEE 12th International Conference on Computer Vision.

[156]  Richard Szeliski,et al.  Reconstructing building interiors from images , 2009, 2009 IEEE 12th International Conference on Computer Vision.

[157]  Richard Szeliski,et al.  Manhattan-world stereo , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.

[158]  T. Kanade,et al.  Geometric reasoning for single image structure recovery , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.

[159]  Richard Szeliski,et al.  Interactive 3D architectural modeling from unordered photo collections , 2008, ACM Trans. Graph..

[160]  P. Olivier,et al.  Camera Control in Computer Graphics , 2008, Comput. Graph. Forum.

[161]  Richard Szeliski,et al.  Modeling the World from Internet Photo Collections , 2008, International Journal of Computer Vision.

[162]  Roberto Cipolla,et al.  Segmentation and Recognition Using Structure from Motion Point Clouds , 2008, ECCV.

[163]  Enrico Gobbetti,et al.  Technical strategies for massive model visualization , 2008, SPM '08.

[164]  Alexei A. Efros,et al.  Recovering Surface Layout from an Image , 2007, International Journal of Computer Vision.

[165]  Reinhard Klein,et al.  Efficient RANSAC for Point‐Cloud Shape Detection , 2007, Comput. Graph. Forum.

[166]  Dieter Fox,et al.  Voronoi Random Fields: Extracting Topological Structure of Indoor Environments via Place Labeling , 2007, IJCAI.

[167]  Honglak Lee,et al.  A Dynamic Bayesian Network Model for Autonomous 3D Reconstruction from a Single Indoor Image , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).

[168]  Richard Szeliski,et al.  A Comparison and Evaluation of Multi-View Stereo Reconstruction Algorithms , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).

[169]  F. Dellaert,et al.  Atlanta world: an expectation maximization framework for simultaneous low-level edge grouping and camera calibration in complex man-made environments , 2004, Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004..

[170]  F. Durand,et al.  A Survey of Visibility for Walkthrough Applications , 2003, IEEE Trans. Vis. Comput. Graph..

[171]  David Harel,et al.  On Clustering Using Random Walks , 2001, FSTTCS.

[172]  Olga Veksler,et al.  Fast approximate energy minimization via graph cuts , 2001, Proceedings of the Seventh IEEE International Conference on Computer Vision.

[173]  Kostas Daniilidis,et al.  A Unifying Theory for Central Panoramic Systems and Practical Applications , 2000, ECCV.

[174]  Ross T. Whitaker,et al.  Indoor scene reconstruction from sets of noisy range images , 1999, Second International Conference on 3-D Digital Imaging and Modeling (Cat. No.PR00062).

[175]  Alan L. Yuille,et al.  Manhattan World: compass direction from a single image by Bayesian inference , 1999, Proceedings of the Seventh IEEE International Conference on Computer Vision.

[176]  Linda G. Shapiro,et al.  Acquisition and visualization of colored 3D objects , 1998, Proceedings. Fourteenth International Conference on Pattern Recognition (Cat. No.98EX170).

[177]  Leonidas J. Guibas,et al.  Optimal Point Location in a Monotone Subdivision , 1986, SIAM J. Comput..

[178]  Raimund Seidel,et al.  Constructing arrangements of lines and hyperplanes with applications , 1983, 24th Annual Symposium on Foundations of Computer Science (sfcs 1983).

[179]  Ruggero Pintus,et al.  Techniques for Seamless Color Registration and Mapping on Dense 3D Models , 2017 .

[180]  Han-Ul Kim,et al.  Accurate Continuous Sweeping Framework in Indoor Spaces With Backpack Sensor System for Applications to 3-D Mapping , 2016, IEEE Robotics and Automation Letters.

[181]  Michael F. Cohen,et al.  Image-Based Remodeling , 2013, IEEE Transactions on Visualization and Computer Graphics.

[182]  Daniel Huber,et al.  Using Context to Create Semantic 3D Models of Indoor Environments , 2010, BMVC.

[183]  Barbara Caputo,et al.  A realistic benchmark for visual indoor place recognition , 2010, Robotics Auton. Syst..

[184]  Benjamin Huhle,et al.  Statistical Reconstruction of Indoor Scenes , 2009 .

[185]  T. Funkhouser,et al.  Eurographics Symposium on Geometry Processing 2014 Piecewise-planar 3d Reconstruction with Edge and Corner Regularization , 2022 .

[186]  Pedro V. Sander,et al.  Eurographics Symposium on Geometry Processing (2005) Progressive Buffers: View-dependent Geometry and Texture Lod Rendering , 2022 .