Conceived, designed and implemented a computer vision algorithm to detect and track golf balls flying downrange up to approximately 50 yards from an iPhone 5 video recording. Reprojected from 2-dimensional video into 3-dimensions, and extrapolated trajectory using Newtonian mechanics and Magnus effect. Achieved performance of 8% average error in tracking ball flight distance compared with gold standard on a sample of swings averaging 150 yards.
All algorithms and software were written in high-performance, cross platform C++ code that runs on iOS, Android, Linux, OS X, and Windows.
- $2500 grant from Yale Entrepreneurship Institute VCP
C++, Python, OpenCV, CMake, Git
Before building a smartphone-based golf ball flight tracker, the plan was to build an inexpensive radar to serve the same purpose. Here is the original slide deck for that idea.