Saliency Identification as a Computational Model of Human Visual Attention
Developing systems inspired by human intelligence was the interest of research for many decades. Human vision is one of the fields the researchers tried to simulate and imitate to develop powerful machine vision systems. This research focuses on the advantages of extracting regions of interest from a scene in reducing the processing power and storage requirements. It explains how the saliency extraction is inspired by human visual attention (HVA) principles and how the computational saliency extraction can be used to simulate these principles. The research includes a brief explanation of HVA and salient point extraction in addition to the relationship between them. Empirical Experiments and results are presented, as well, to support the discussion and the aim of this research.