Analyzing the impact of the initialization for the nonnegative tensor factorization in tensor displays

Abstract

Tensor display is an option in glasses-free three-dimensional (3-D) display technology. An initial solution has to be set to decompose the light-field information to be represented by the system. We have analyzed the impact of the initial guess on the multiplicative update rules in terms of peak signal-to-noise ratio, and proposed a method based on depth map estimation from an input light field. Results from simulations were obtained and compared with previous literature. In our sample, the initial values used have a large influence on results and convergence to a local minimum. The quality of the output stabilizes after a certain number of iterations, suggesting that a limit on such numbers should be imposed. We show that the proposed methods outperform the pre-existing ones.