Obtaining Discriminative Colour Names According to the Context: Using a Fuzzy Colour Model and Probabilistic Reference Grounding

In human-machine communication situations, perceptual and conceptual deviations can appear. The challenge of categorising colours is tackled in this paper. Colour perception is very subjective. Colours may be perceived differently depending on a person's eye anatomy and a person's sense of sight which adapts to the surroundings and perceives different brightness of hues depending on the context. Distinguishing more/less quantity of hues depends also on the level of expertise but also on the cultural and social environment. Colours naming involves conceptual alignment with human cognition, meaning and human understanding for referring to an object and even for discriminating among objects. Studies in cross-cultural linguistics say that humans determined prototypical colours as the centre of colour categories. (1) Hence, a cognitive colour model should distinguish/indicate when a colour coordinate is close/far to the centre of its category. And these centres of categories should be adaptable and customisable depending on the society. A fuzzy colour model based on HSL colour space and radial basis functions is presented in this paper. Logics have been defined to combine this fuzzy-colour model with a Probabilistic Reference And GRounding mechanism (PRAGR)(2) in order to obtain the most discriminative colour descriptor for an object depending on the context. Two case studies related with human cognition are presented. Then further tests are carried out on a dataset where the first and second most discriminative colour is computed for each object in each scene. Finally, a survey is conducted to find out the cognitive adequacy of the obtained discriminative colour names.