Connected-component stereo aggregation

Stereo vision algorithms can be divided into several general stages. Detailed analysis on each specific stage allows focused improvement of the entire algorithm. Existing stereo vision algorithms typically prioritize pixel and sub-pixel accuracy, focusing on the optimization stage, while commercial algorithms which prioritize real-time operation typically focus on the cost calculation stage. This paper presents a novel approach to cost aggregation, a module within the cost calculation stage, based on connected-component analysis. The conventional connected-component analysis algorithm is extended for use in the stereo vision matching cost aggregation problem, resulting in an algorithm which is comparable in efficiency to the best current aggregation algorithms while performing well at object boundaries, typically the most difficult problem for aggregation-based approaches.