Add code; Modify README.md

Author: PeiliangLi

.gitignore

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+VINS_ThirdPartyLib/opencv2.framework
+
+.DS_Store
+*.swp
+# Xcode
+#
+# gitignore contributors: remember to update Global/Xcode.gitignore, Objective-C.gitignore & Swift.gitignore
+
+## Build generated
+build/
+DerivedData/
+
+## Various settings
+*.pbxuser
+!default.pbxuser
+*.mode1v3
+!default.mode1v3
+*.mode2v3
+!default.mode2v3
+*.perspectivev3
+!default.perspectivev3
+xcuserdata/
+
+## Other
+*.moved-aside
+*.xccheckout
+*.xcscmblueprint
+>>>>>>> [Unity] Add Unity project

LICENSE

@@ -1 +1,52 @@
 # VINS-Mobile
+## Monocular Visual-Inertial State Estimator on Mobile Phones
+
+VINS-Mobile is a real-time monocular visual-inertial state estimator developed by members of the [HKUST Aerial Robotics Group](http://uav.ust.hk/). It runs on compatible iOS devices, and provides localization services for augmented reality (AR) applications. It is also tested for state estimation and feedback control for autonomous drones. VINS-Mobile uses sliding window optimization-based formulation for providing high-accuracy visual-inertial odometry with automatic initialization and failure recovery. The accumulated odometry errors are corrected in real-time using global pose graph SLAM. An AR demonstration is provided to showcase its capability.
+
+**Authors:** Peiliang LI, Tong QIN, Zhenfei YANG, Kejie QIU, and [Shaojie SHEN](http://www.ece.ust.hk/ece.php/profile/facultydetail/eeshaojie) from the [HKUST Aerial Robotics Group](http://uav.ust.hk/)
+
+**Videos:** https://www.youtube.com/watch?v=qazzGT84Scc&feature=youtu.be
+
+**Related Papers:**
+* [**Monocular Visual-Inertial State Estimation for Mobile Augmented Reality**](http://www.ece.ust.hk/~eeshaojie/ismar2017peiliang.pdf), *P.Li et al (submitted to ISMAR 2017)*
+* [**Robust Initialization of Monocular Visual-Inertial Estimation on Aerial Robots**](http://www.ece.ust.hk/~eeshaojie/iros2017tong.pdf), *T.Qin et al (submitted to IROS 2017)*
+* [**Monocular Visual-Inertial State Estimation With Online Initialization and Camera-IMU Extrinsic Calibration**](http://ieeexplore.ieee.org/document/7463059/), *Z.Yang et al (T-ASE 2017)*
+
+*If you use VINS-Mobile for your academic research, please cite at least one of our related papers.*
+
+## 1. Build
+
+The code has been compiled on macOS Sierra with Xcode 8.3.1 and tested with iOS 10.2.1 on iPhone7 Plus.
+
+1.1 Install boost for macOS
+```
+	$ ruby -e "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/master/install)"
+	$ brew install boost
+```
+1.2 Download specific **opencv2.framework** from [here](https://www.dropbox.com/sh/r28gjnue98ro1fa/AACiEH-HUdZxU4852_AytAPPa?dl=0)
+
+1.3 Copy the **opencv2.framework** to **VINS_ThirdPartyLib/opencv2.framework**
+
+1.4 In your Xcode, select **Product**-> **Scheme**-> **Edit Scheme**-> **Run**-> **Info**, set **Build Configuration** to **Release**
+
+1.5 Build and Run
+
+1.6 Compatible Devices
+
+	iPhone7 Plus, iPhone7, iPhone6s Plus, iPhone6s
+	
+If you use it with non-plus devices, you may need to modify the UI size at Main.storyboard for adapting with your screen.
+
+## 2. Acknowledgements
+
+We use [ceres solver](http://ceres-solver.org/) for non-linear optimization and [DBow](https://github.com/dorian3d/DBoW2) for loop detection.
+
+Thanks [Yang Liu](https://github.com/wandermyz) to contribute to this code.
+
+## 3. Licence
+
+The source code is released under [GPLv3](http://www.gnu.org/licenses/) licence.
+
+We are still working for improving the code readability. Welcome to contribute to VINS-Mobile or ask any issues via Github or contacting Peiliang LI <[email protected]> or Tong QIN <[email protected]>.
+
+For commercial inqueries, please contact Shaojie SHEN <[email protected]>