Case study of autostereoscopic image based on SIRDS algorithm

Abstract

Single Image Random Dots Stereogram (SIRDS) is an interesting algorithm deployed to represent a three-dimensional scene. Results of the algorithm are normal two-dimensional pictures but they do carry the vivid depth information - the third dimension in the real three-dimensional world - that cannot be obtained explicitly with other traditional two-dimensional pictures. The novelties of this paper are twofold: first it gives readers a complete overview of the possibility of `seeing´ reconstructed three-dimensional objects; then the paper focuses on analyzing and improving the implementation of the SIRDS algorithm. Its drawbacks and, especially, its visibility are deeply discussed and tested. Our proposals for generating optimized autostereograms (products of SIRDS) - i.e. they clearly display the depth information of a scene with less artifact and easier to view - are also presented.