Implemented keypoint detectors, descriptors, and methods to match them between successive images. Detected objects in an image using the YOLO deep-learning framework. And finally, associate regions in a camera image with Lidar points in 3D space. Using that Lidar points and the keypoints inside the reigon of intrest in the camera calculated Time To Collision (TTC). Below is the program schematic.
- 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
- OpenCV >= 4.1
- This must be compiled from source using the
-D OPENCV_ENABLE_NONFREE=ONcmake 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.