Abstract Depth map extraction or estimation is very important for many computer vision applications. However, this process involves high cost. Hence, it is interesting to find new approaches, which could yield faster implementations, when very accurate results are not necessary.
These new implementations can be built up for the stereovision problem, taking advantage of the specific geometrical constraints of this kind of problem. The problem is solved by searching pixel-by-pixel matching in horizontal lines. In this article, we propose a novel approach to this problem,
providing measurements of the processing time and accuracy achieved, as well as a qualitative comparison with other methods available in the literature. The results obtained could reach speeds around one order of magnitude faster than those proposed in other classical implementations. Thus,
the proposed algorithm can run on cheap and low-performance hardware achieving real-time processing rates.