This project approaches the design of a collision detection system based on motion models, lidar, and camera measurements from the benchmark KITTI dataset:
- Detect and track objects from the benchmark KITTI dataset.
- Classify those objects and project them into three dimensions.
- Fuse those projections together with lidar data to create 3D objects to track over time and compute time-to-collision based on both sensors.
- 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
- This must be compiled from source using the
- 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
- Clone this repo.
- Make a build directory in the top level project directory:
mkdir build && cd build
- Compile:
cmake .. && make
- Run it:
./3D_object_tracking
.