cjchng · M11158002 · Mar 25, 2020 · Mar 31, 2020 · Mar 31, 2020 · Mar 31, 2020
diff --git a/1910.01122.pdf b/1910.01122.pdf
diff --git a/README.md b/README.md
@@ -1,137 +1,32 @@
-<p align="center">
-<img src="https://raw.githubusercontent.com/xdspacelab/openvslam/master/docs/img/logo.png" width="435px">
-</p>
+# Hi
 
-# OpenVSLAM: A Versatile Visual SLAM Framework
-[![Wercker Status](https://app.wercker.com/status/8b02a43f48216385658bb3857aae5fd8/s/master)](https://app.wercker.com/shinsumicco/openvslam/runs)
-[![Travis CI Status](https://api.travis-ci.org/xdspacelab/openvslam.svg?branch=master)](https://travis-ci.org/xdspacelab/openvslam)
-[![Documentation Status](https://readthedocs.org/projects/openvslam/badge/?version=master)](https://openvslam.readthedocs.io/)
-[![Docker Build Status](https://img.shields.io/docker/cloud/build/shinsumicco/openvslam.svg)](https://hub.docker.com/r/shinsumicco/openvslam)
-[![License](https://img.shields.io/badge/License-BSD%202--Clause-orange.svg)](https://opensource.org/licenses/BSD-2-Clause)
+## 相機校準
 
-## Overview
+可以使用OpenCV的方法校準
 
-[<img src="https://raw.githubusercontent.com/xdspacelab/openvslam/master/docs/img/teaser.png" width="640px">](https://arxiv.org/abs/1910.01122)
+- How to Calibrate a Monocular Camera(單鏡頭相機)
 
-[<img src="https://raw.githubusercontent.com/wiki/xdspacelab/openvslam/media/tracking.gif" width="640px">](https://www.youtube.com/watch?v=Ro_s3Lbx5ms)
+  - <http://wiki.ros.org/camera_calibration/Tutorials/MonocularCalibration>
 
-[**[PrePrint]**](https://arxiv.org/abs/1910.01122) [**[YouTube]**](https://www.youtube.com/watch?v=Ro_s3Lbx5ms)
+- How to Calibrate a Stereo Camera(立體鏡頭相機)
 
-OpenVSLAM is a monocular, stereo, and RGBD visual SLAM system.
-The notable features are:
+  - <http://wiki.ros.org/camera_calibration/Tutorials/StereoCalibration>
 
-- It is compatible with **various type of camera models** and can be easily customized for other camera models.
-- Created maps can be **stored and loaded**, then OpenVSLAM can **localize new images** based on the prebuilt maps.
-- The system is fully modular. It is designed by encapsulating several functions in separated components with easy-to-understand APIs.
-- We provided **some code snippets** to understand the core functionalities of this system.
+## 跑在 Docker 的 ROS and OpenVSLAM
 
-OpenVSLAM is based on an indirect SLAM algorithm with sparse features, such as ORB-SLAM, ProSLAM, and UcoSLAM.
-One of the noteworthy features of OpenVSLAM is that the system can deal with various type of camera models, such as perspective, fisheye, and equirectangular.
-If needed, users can implement extra camera models (e.g. dual fisheye, catadioptric) with ease.
-For example, visual SLAM algorithm using **equirectangular camera models** (e.g. RICOH THETA series, insta360 series, etc) is shown above.
+ Running ROS package of openvslam on Docker
 
-Some code snippets to understand the core functionalities of the system are provided.
-You can employ these snippets for in your own programs.
-Please see the `*.cc` files in `./example` directory or check [Simple Tutorial](https://openvslam.readthedocs.io/en/master/simple_tutorial.html) and [Example](https://openvslam.readthedocs.io/en/master/example.html).
+- <https://github.com/Taka-Kazu/openvslam/tree/add-ros-dockerfile>
 
-We provided [documentation](https://openvslam.readthedocs.io/) for installation and tutorial.
-Please contact us via [GitHub issues](https://github.com/xdspacelab/openvslam/issues) if you have any questions or notice any bugs about the software.
+## OpenVSLAM
 
-## Motivation
+- dbow2
+  - <https://github.com/shinsumicco/DBoW2>
+- fbow
+  - <https://github.com/rmsalinas/fbow>
 
-Visual SLAM is regarded as a next-generation technology for supporting industries such as automotives, robotics, and xR. 
-We released OpenVSLAM as an opensource project with the aim of collaborating with people around the world to accelerate the development of this field.
-In return, we hope this project will bring safe and reliable technologies for a better society.
+## openvslam cuda
 
-## Installation
+## USB攝像機實時計算
 
-Please see [**Installation**](https://openvslam.readthedocs.io/en/master/installation.html) chapter in the [documentation](https://openvslam.readthedocs.io/).
-
-[**The instructions for Docker users**](https://openvslam.readthedocs.io/en/master/docker.html) are also provided.
-
-## Tutorial
-
-Please see [**Simple Tutorial**](https://openvslam.readthedocs.io/en/master/simple_tutorial.html) chapter in the [documentation](https://openvslam.readthedocs.io/).
-
-A sample ORB vocabulary file can be downloaded from [here](https://drive.google.com/open?id=1wUPb328th8bUqhOk-i8xllt5mgRW4n84).
-Sample datasets are also provided at [here](https://drive.google.com/open?id=1A_gq8LYuENePhNHsuscLZQPhbJJwzAq4).
-
-If you would like to run visual SLAM with standard benchmarking datasets (e.g. KITTI Odometry dataset), please see [**SLAM with standard datasets**](https://openvslam.readthedocs.io/en/master/example.html#slam-with-standard-datasets) section in the [documentation](https://openvslam.readthedocs.io/).
-
-## Community
-
-If you want to join our Slack community, please fill out the application form from the following site(s):
-
-- [http://bit.ly/openvslam](http://bit.ly/openvslam)
-- [http://bit.ly/openvslam-jp](http://bit.ly/openvslam-jp) (日本語: in Japanese)
-
-## Currently working on
-
-- IMU integration
-- Python bindings
-- Implementation of extra camera models
-- Refactoring
-
-Feedbacks, feature requests, and contribution are welcome!
-
-## License
-
-**2-clause BSD license** (see [LICENSE](./LICENSE))
-
-The following files are derived from third-party libraries.
-
-- `./3rd/json` : [nlohmann/json \[v3.6.1\]](https://github.com/nlohmann/json) (MIT license)
-- `./3rd/popl` : [badaix/popl \[v1.2.0\]](https://github.com/badaix/popl) (MIT license)
-- `./3rd/spdlog` : [gabime/spdlog \[v1.3.1\]](https://github.com/gabime/spdlog) (MIT license)
-- `./src/openvslam/solver/pnp_solver.cc` : part of [laurentkneip/opengv](https://github.com/laurentkneip/opengv) (3-clause BSD license)
-- `./src/openvslam/feature/orb_extractor.cc` : part of [opencv/opencv](https://github.com/opencv/opencv) (3-clause BSD License)
-- `./src/openvslam/feature/orb_point_pairs.h` : part of [opencv/opencv](https://github.com/opencv/opencv) (3-clause BSD License)
-- `./viewer/public/js/lib/dat.gui.min.js` : [dataarts/dat.gui](https://github.com/dataarts/dat.gui) (Apache License 2.0)
-- `./viewer/public/js/lib/protobuf.min.js` : [protobufjs/protobuf.js](https://github.com/protobufjs/protobuf.js) (3-clause BSD License)
-- `./viewer/public/js/lib/stats.min.js` : [mrdoob/stats.js](https://github.com/mrdoob/stats.js) (MIT license)
-- `./viewer/public/js/lib/three.min.js` : [mrdoob/three.js](https://github.com/mrdoob/three.js) (MIT license)
-
-Please use `g2o` as the dynamic link library because `csparse_extension` module of `g2o` is LGPLv3+.
-
-## Contributors
-
-- Shinya Sumikura ([@shinsumicco](https://github.com/shinsumicco))
-- Mikiya Shibuya ([@MikiyaShibuya](https://github.com/MikiyaShibuya))
-- Ken Sakurada ([@kensakurada](https://github.com/kensakurada))
-
-## Citation
-
-OpenVSLAM **won first place** at **ACM Multimedia 2019 Open Source Software Competition**.
-
-If OpenVSLAM helps your research, please cite the paper for OpenVSLAM. Here is a BibTeX entry:
-
-```
-@inproceedings{openvslam2019,
-  author = {Sumikura, Shinya and Shibuya, Mikiya and Sakurada, Ken},
-  title = {{OpenVSLAM: A Versatile Visual SLAM Framework}},
-  booktitle = {Proceedings of the 27th ACM International Conference on Multimedia},
-  series = {MM '19},
-  year = {2019},
-  isbn = {978-1-4503-6889-6},
-  location = {Nice, France},
-  pages = {2292--2295},
-  numpages = {4},
-  url = {http://doi.acm.org/10.1145/3343031.3350539},
-  doi = {10.1145/3343031.3350539},
-  acmid = {3350539},
-  publisher = {ACM},
-  address = {New York, NY, USA}
-}
-```
-
-The preprint can be found [here](https://arxiv.org/abs/1910.01122).
-
-## Reference
-
-- Raúl Mur-Artal, J. M. M. Montiel, and Juan D. Tardós. 2015. ORB-SLAM: a Versatile and Accurate Monocular SLAM System. IEEE Transactions on Robotics 31, 5 (2015), 1147–1163.
-- Raúl Mur-Artal and Juan D. Tardós. 2017. ORB-SLAM2: an Open-Source SLAM System for Monocular, Stereo and RGB-D Cameras. IEEE Transactions on Robotics 33, 5 (2017), 1255–1262.
-- Dominik Schlegel, Mirco Colosi, and Giorgio Grisetti. 2018. ProSLAM: Graph SLAM from a Programmer’s Perspective. In Proceedings of IEEE International Conference on Robotics and Automation (ICRA). 1–9.
-- Rafael Muñoz-Salinas and Rafael Medina Carnicer. 2019. UcoSLAM: Simultaneous Localization and Mapping by Fusion of KeyPoints and Squared Planar Markers. arXiv:1902.03729.
-- Mapillary AB. 2019. OpenSfM. https://github.com/mapillary/OpenSfM.
-- Giorgio Grisetti, Rainer Kümmerle, Cyrill Stachniss, and Wolfram Burgard. 2010. A Tutorial on Graph-Based SLAM. IEEE Transactions on Intelligent Transportation SystemsMagazine 2, 4 (2010), 31–43.
-- Rainer Kümmerle, Giorgio Grisetti, Hauke Strasdat, Kurt Konolige, and Wolfram Burgard. 2011. g2o: A general framework for graph optimization. In Proceedings of IEEE International Conference on Robotics and Automation (ICRA). 3607–3613.
+- <https://github.com/xdspacelab/openvslam/blob/master/example/run_camera_localization.cc>