On motion estimation

【鱼眼相机】

  1. OpenCV 中的标定:http://docs.opencv.org/master/db/d58/group__calib3d__fisheye.html

【视觉人物】

【视觉人物】

  1. Light fields – the future of VR-AR-MR
    1. https://www.fxguide.com/featured/light-fields-the-future-of-vr-ar-mr/
  2. Augmented Reality: The Past, Present, and Future
    1. https://binocular.io/insights/augmented-reality-the-past-present-and-future
  3. Richard Newcombe http://homes.cs.washington.edu/~newcombe/
    1. 2015 CVPR DynamicFusion: Reconstruction and Tracking of Non-rigid Scenes in Real-Time
    2. 2011 CVPR KinectFusion: Real-Time Dense Surface Mapping and Tracking
  4. Pierre Moulon http://imagine.enpc.fr/~moulonp/ Renaud MARLET http://imagine.enpc.fr/~marletr/
    1. 2013 ICCV Global Fusion of Relative Motions for Robust, Accurate and Scalable Structure from Motion
    2. 2012 ACCV Adaptive Structure from Motion with a contrario model estimation
  5. Torsten Sattler: http://people.inf.ethz.ch/sattlert/
    1. https://wp.doc.ic.ac.uk/thefutureofslam/ The Future of Real-Time SLAM
    2. 2015 ICCV Non-Parametric Structure-Based Calibration of Radially Symmetric Cameras
    3. 2015 ICCV Camera Pose Voting for Large-Scale Image-Based Localization
    4. 2014 ECCV Scalable 6-DOF Localization on Mobile Devices
  6. In So Kweon: http://rcv.kaist.ac.kr/
    1. 2015 ICCV Accurate Camera Calibration Robust to Defocus using a Smartphone
    2. 2015 ICCV High Quality Structure from Small Motion for Rolling Shutter Cameras
  7. Marc Pollefeys https://www.inf.ethz.ch/personal/pomarc/
    1. 2015 ICCV Camera Pose Voting for Large-Scale Image-Based Localization
    2. 2014 3DTV Two Cameras and a Screen: How to Calibrate Mobile Devices?
  8. Four Eyes Lab: http://ilab.cs.ucsb.edu/index.php/ , Chris Sweeney http://cs.ucsb.edu/~cmsweeney/
    1. http://ilab.cs.ucsb.edu/index.php/component/content/article/10/151 2012 ISMAR Live Tracking and Mapping from Both General and Rotation-Only Camera Motion
    2. 2015 ISMAR Efficient Computation of Absolute Pose for Gravity-Aware Augmented Reality
    3. 2014 ECCV On Sampling Focal Length Values to Solve the Absolute Pose Problem
  9. Guofeng Zhang: http://www.cad.zju.edu.cn/home/gfzhang/
    1. Large-Scale Automatic Camera Tracking System
    2. Robust Dynamic Simultaneous Localization and Mapping
    3. Automatic Camera Tracking System
    4. 2014 CVIU Efficient Keyframe-Based Real-Time Camera Tracking
    5. 2013 ISMAR Robust Monocular SLAM in Dynamic Environments
  10. ICGV, Tu Graz: http://www.icg.tugraz.at/publications
    1. 2015 ISMAR Instant Outdoor Localization and SLAM Initialization from 2.5D Maps, http://studierstube.icg.tugraz.at/handheld_ar/hybrid_slam.php
    2. 2013 ISMAR Handling Pure Camera Rotation in Keyframe-Based SLAM
  11. Leap Motion: https://www.leapmotion.com/
  12. Magic Leap: http://www.magicleap.com/
  13. FaceBook: Surreal Vision Ltd http://www.doc.ic.ac.uk/~rfs09/index.html
  14. Andrew Davison http://www.doc.ic.ac.uk/~ajd/
    1. 2013 CVPR SLAM++: Simultaneous Localisation and Mapping at the Level of Objects
    2. 2014 ISMAR: Dense Planar SLAM
  15. Daniel Cremers: http://vision.in.tum.de/
    1. 2015 ICCV Model-Based Tracking at 300Hz using Raw Time-of-Flight Observations
    2. 2015 ICCV Dense Continuous-Time Tracking and Mapping with Rolling Shutter RGB-D Cameras
    3. 2015 IROS Large-Scale Direct SLAM with Stereo Cameras
    4. 2014 ISMAR Semi-Dense Visual Odometry for AR on a Smartphone
  16. Jan-Michael Frahm: http://frahm.web.unc.edu/, Jan-Michael Frahm http://www.cs.unc.edu/~jmf/RotCali.html
    1. Rotation Estimation from Cloud Tracking
    2. Camera-Self calibration with additional sensory information
  17. Greg Welch: http://www.cs.unc.edu/~welch/ , Feng Zheng: http://www.cs.unc.edu/~zhengf/
    1. 2015 PhD thesis Spatio-Temporal Registration in Augmented Reality