  With the developments of dual-lens camera modules,depth information
representing the third dimension of thecaptured scenes becomes available for
smartphones. It isestimated by stereo matching algorithms, taking as input
thetwo views captured by dual-lens cameras at slightly differ-ent viewpoints.
Depth-of-field rendering (also be referred toas synthetic defocus or bokeh) is
one of the trending depth-based applications. However, to achieve fast depth
estima-tion on smartphones, the stereo pairs need to be rectified inthe first
place. In this paper, we propose a cost-effective so-lution to perform stereo
rectification for dual-lens camerascalled direct self-rectification, short for
DSR1. It removesthe need of individual offline calibration for every pair
ofdual-lens cameras. In addition, the proposed solution isrobust to the slight
movements, e.g., due to collisions, ofthe dual-lens cameras after fabrication.
Different with ex-isting self-rectification approaches, our approach
computesthe homography in a novel way with zero geometric distor-tions
introduced to the master image. It is achieved by di-rectly minimizing the
vertical displacements of correspond-ing points between the original master
image and the trans-formed slave image. Our method is evaluated on both
real-istic and synthetic stereo image pairs, and produces supe-rior results
compared to the calibrated rectification or otherself-rectification approaches
