Prediction of visual attention with Deep CNN for studies of neurodegenerative diseases

As a part of the automatic study of visual attention of affected populations with neurodegenerative diseases and to predict whether new gaze records a complaint of these diseases, we should design an automatic model that predicts salient areas in video. Past research showed, that people suffering form dementia are not reactive with regard to degradations on still images. In this paper we study the reaction of healthy normal control subjects on degraded area in videos. Furthermore, in the goal to build an automatic prediction model for salient areas in intentionally degraded videos, we design a deep learning architecture and measure its performances when predicting salient regions on completely unseen data. The obtained results are interesting regarding the reaction of normal control subjects against a degraded area in video.