A SIFT descriptor based method for global disparity vector estimation in multiview video coding

Disparity estimation is crucial to multiview video coding (MVC), which has attracted much attention recently. In the MVC reference software, named JMVM, the global disparity vector (GDV) was estimated by frame matching on spatial neighbor views. In this paper, a scale invariant feature transform (SIFT) based disparity estimation method is proposed to estimate the GDV. The experimental results show that benefits on peak signal-to-noise ratio (PSNR) and saved bits can be obtained by adopting our proposed method compared to the JMVM method that was often used.