Adapting hierarchical ALS algorithms for temporal psychovisual modulation
Temporal psychovisual modulation (TPVM) is a new information display technology, which aims to generate multiple visual percepts for different viewers on a single display simultaneously. In TPVM system, the viewers with different active liquid crystal (LC) glasses (i.e., different modulation weights) which are synchronized with the display can see different images (called personal views). TPVM can be implemented by nonnegative matrix factorization (NMF) with three additional constrains: the values of images and modulation weights should have upper bound; a special view (called shared view) without using viewing devices should be considered (i.e., the sum of all basis images should be a meaningful image); the sparsity of modulation weights should be considered because of the material property of LC. In this paper, we solve the constrained NMF problem by the modified hierarchical alternating least squares (HALS) algorithms. Through experiments, we analyse the influence of different parameters of TPVM to provide a guideline for parameter selection. This paper will provide an algorithmic guidance for the applications of TPVM.