Stereo matching is a fundamental problem in computer vision and understanding how different approaches relate to one another can provide valuable insight into the field. In this post, I’m sharing a repository that presents simplified implementations of several classic stereo matching algorithms (in MATLAB and Python), making it easier to study their underlying concepts and compare their implementations.
The project includes Block Matching, Dynamic Programming, Semi-Global Matching and two variants of Belief Propagation (Directional and Synchronous). Rather than focusing solely on the final algorithms, the implementations have been simplified and adapted to highlight the connections between them. This allows readers to follow how ideas from one method can lead to the next and gain a clearer understanding of the evolution of stereo matching techniques.
Repository: Basic Stereo Algorithms (Evolution)
