A novel heterogeneous framework for stereo matching
Local stereo matching algorithms based on the adapting-weights strategy achieve accuracy similar to global approaches. One of the major problems of these local algorithms is that they are computationally expensive. However, algorithms with reduced computational complexity inspired by the adapting-weights strategy have been recently proposed. In particular, the Fast Bilateral Stereo (FBS) framework allows to obtain, with a significantly reduced computational burden, results comparable to top-performing local approaches based on adapting-weights. In this paper we propose a novel framework that has two advantages: enables a further speedup of this type of algorithms along with a slight accuracy improvement. We prove the effectiveness of our proposal in combination with the FBS approach.
