manankshastri / 3D-Object-Tracking-and-Estimation-of-TTC

Tracking of 3D Bounding boxes and computation of time-to-collision using LiDAR and Camera

3D Object Tracking and Estimation of Time-To-Collision

Result

(SIFT/FREAK)

Ther are four major tasks:

1. First, we will develop a way to match 3D objects over time by using keypoint correspondences.
2. Second, we will compute the TTC based on Lidar measurements.
3. We will then proceed to do the same using the camera, which requires to first associate keypoint matches to regions of interest and then to compute the TTC based on those matches.
4. And lastly, we will conduct various tests with the framework. The goal is to identify the most suitable detector/descriptor combination for TTC estimation and also to search for problems that can lead to faulty measurements by the camera or Lidar sensor.

Dependencies for Running Locally

• cmake >= 2.8
  • All OSes: click here for installation instructions
• make >= 4.1 (Linux, Mac), 3.81 (Windows)
  • Linux: make is installed by default on most Linux distros
  • Mac: install Xcode command line tools to get make
  • Windows: Click here for installation instructions
• Git LFS
  • Weight files are handled using LFS
• OpenCV >= 4.1
  • This must be compiled from source using the -D OPENCV_ENABLE_NONFREE=ON cmake flag for testing the SIFT and SURF detectors.
  • The OpenCV 4.1.0 source code can be found here
• gcc/g++ >= 5.4
  • Linux: gcc / g++ is installed by default on most Linux distros
  • Mac: same deal as make - install Xcode command line tools
  • Windows: recommend using MinGW

Basic Build Instructions

1. Clone this repo.
2. Make a build directory in the top level project directory: mkdir build && cd build
3. Compile: cmake .. && make
4. Run it: ./3D_object_tracking.