EMOTIF - A system for modeling 3D environment evaluation based on 7D emotional vectors

It is widely known that the decisions being made concern objects representing a set of characteristics whose importance is unique for every decision-maker. However, including this aspect in analyses is a challenge for many researchers. Classically applied information analysis methods fail to consider the synergy of these characteristics and ignore the impact of behavioural aspects that are inseparable from the decision-maker. The study proposed a solution based on an emotion detection technology using Computer Vision and Neural Networks. The presented approach comprises three main components: the detection of emotions using CNN - acquiring input vector value elements to the model for evaluation of space features; MLP for the assessment of anthropogenic and natural space features; and the verification of the utilitarian nature, usability, and suitability for the use of the developed solution. The novelty of the paper relates to the proposition of the new approaches by demonstrating that the assessment of the impact of an object's features is a synergistic, inseparable conglomerate (Fusion Features), which thus indicates the greater usability of the results such studies in the analysis of a particular phenomenon, structure, or system.