Ninth International Conference on Communication & Media Studies

Abstract

In visual cognition research, saliency refers to the prominence of specific elements in a scene. Moreover, saliency guidance is part of a filmmaker’s toolset to build narratives and guide the audience into emotive responses, transforming it into a cinematic narrative tool. This paper compares two CNN (Convolutional Neural Network) saliency mapping models with viewers’ eye-position mapping to investigate the potentiality of automated saliency mapping in moving image studies by analyzing saliency role during cinema’s transition from one-shot to multiple-shot. Although the exact moment when montage and editing methods appeared cannot be pointed out with precision, one of the reasons for this transition was saliency guidance, hence its preponderance.