Fix markdown issues

README.md

@@ -15,15 +15,15 @@ alt="ORB-SLAM2" width="240" height="180" border="10" /></a>
 alt="ORB-SLAM2" width="240" height="180" border="10" /></a>
 
 
-###Related Publications:
+### Related Publications:
 
 [Monocular] Raúl Mur-Artal, J. M. M. Montiel and Juan D. Tardós. **ORB-SLAM: A Versatile and Accurate Monocular SLAM System**. *IEEE Transactions on Robotics,* vol. 31, no. 5, pp. 1147-1163, 2015. (**2015 IEEE Transactions on Robotics Best Paper Award**). **[PDF](http:https://webdiis.unizar.es/~raulmur/MurMontielTardosTRO15.pdf)**.
 
 [Stereo and RGB-D] Raúl Mur-Artal and Juan D. Tardós. **ORB-SLAM2: an Open-Source SLAM System for Monocular, Stereo and RGB-D Cameras**. *ArXiv preprint arXiv:1610.06475* **[PDF](https://128.84.21.199/pdf/1610.06475.pdf)**.
 
 [DBoW2 Place Recognizer] Dorian Gálvez-López and Juan D. Tardós. **Bags of Binary Words for Fast Place Recognition in Image Sequences**. *IEEE Transactions on Robotics,* vol. 28, no. 5, pp. 1188-1197, 2012. **[PDF](http:https://doriangalvez.com/php/dl.php?dlp=GalvezTRO12.pdf)**
 
-#1. License
+# 1. License
 
 ORB-SLAM2 is released under a [GPLv3 license](https://github.com/raulmur/ORB_SLAM2/blob/master/License-gpl.txt). For a list of all code/library dependencies (and associated licenses), please see [Dependencies.md](https://github.com/raulmur/ORB_SLAM2/blob/master/Dependencies.md).
 
@@ -51,7 +51,7 @@ if you use ORB-SLAM2 (Stereo or RGB-D) in an academic work, please cite:
   year={2016}
   }
 
-#2. Prerequisites
+# 2. Prerequisites
 We have tested the library in **Ubuntu 12.04**, **14.04** and **16.04**, but it should be easy to compile in other platforms. A powerful computer (e.g. i7) will ensure real-time performance and provide more stable and accurate results.
 
 ## C++11 or C++0x Compiler
@@ -72,7 +72,7 @@ We use modified versions of the [DBoW2](https://github.com/dorian3d/DBoW2) libra
 ## ROS (optional)
 We provide some examples to process the live input of a monocular, stereo or RGB-D camera using [ROS](ros.org). Building these examples is optional. In case you want to use ROS, a version Hydro or newer is needed.
 
-#3. Building ORB-SLAM2 library and TUM/KITTI examples
+# 3. Building ORB-SLAM2 library and examples
 
 Clone the repository:
 ```
@@ -88,7 +88,7 @@ chmod +x build.sh
 
 This will create **libORB_SLAM2.so** at *lib* folder and the executables **mono_tum**, **mono_kitti**, **rgbd_tum**, **stereo_kitti**, **mono_euroc** and **stereo_euroc** in *Examples* folder.
 
-#4. Monocular Examples
+# 4. Monocular Examples
 
 ## TUM Dataset
 
@@ -121,7 +121,7 @@ This will create **libORB_SLAM2.so** at *lib* folder and the executables **mono
 ./Examples/Monocular/mono_euroc Vocabulary/ORBvoc.txt Examples/Monocular/EuRoC.yaml PATH_TO_SEQUENCE/cam0/data Examples/Monocular/EuRoC_TimeStamps/SEQUENCE.txt 
 ```
 
-#5. Stereo Examples
+# 5. Stereo Examples
 
 ## KITTI Dataset
 
@@ -144,7 +144,7 @@ This will create **libORB_SLAM2.so** at *lib* folder and the executables **mono
 ./Examples/Stereo/stereo_euroc Vocabulary/ORBvoc.txt Examples/Stereo/EuRoC.yaml PATH_TO_SEQUENCE/cam0/data PATH_TO_SEQUENCE/cam1/data Examples/Stereo/EuRoC_TimeStamps/SEQUENCE.txt
 ```
 
-#6. RGB-D Example
+# 6. RGB-D Example
 
 ## TUM Dataset
 
@@ -162,7 +162,7 @@ This will create **libORB_SLAM2.so** at *lib* folder and the executables **mono
  ./Examples/RGB-D/rgbd_tum Vocabulary/ORBvoc.txt Examples/RGB-D/TUMX.yaml PATH_TO_SEQUENCE_FOLDER ASSOCIATIONS_FILE
  ```
 
-#7. ROS Examples
+# 7. ROS Examples
 
 ### Building the nodes for mono, monoAR, stereo and RGB-D
 1. Add the path including *Examples/ROS/ORB_SLAM2* to the ROS_PACKAGE_PATH environment variable. Open .bashrc file and add at the end the following line. Replace PATH by the folder where you cloned ORB_SLAM2:
@@ -222,10 +222,10 @@ For an RGB-D input from topics `/camera/rgb/image_raw` and `/camera/depth_regist
  rosrun ORB_SLAM2 RGBD PATH_TO_VOCABULARY PATH_TO_SETTINGS_FILE
  ```
 
-#8. Processing your own sequences
+# 8. Processing your own sequences
 You will need to create a settings file with the calibration of your camera. See the settings file provided for the TUM and KITTI datasets for monocular, stereo and RGB-D cameras. We use the calibration model of OpenCV. See the examples to learn how to create a program that makes use of the ORB-SLAM2 library and how to pass images to the SLAM system. Stereo input must be synchronized and rectified. RGB-D input must be synchronized and depth registered.
 
-#9. SLAM and Localization Modes
+# 9. SLAM and Localization Modes
 You can change between the *SLAM* and *Localization mode* using the GUI of the map viewer.
 
 ### SLAM Mode