Energy-based iterative cost aggregation in depth estimation with a stereo camera
This paper presents a novel algorithm for performing an efficient cost aggregation in stereo vision. The cost aggregation is re-formulated under an iterative framework with a perspective of an energy model. The convergence of global energy is exploited to calculate the number of the iterations in cost aggregation. Experimental results show that the proposed method improves the quality of the disparity.