0000000000700956
AUTHOR
Maria Petrou
A fuzzy approach to the evaluation of image complexity
The inherently multidimensional problem of evaluating the complexity of an image is of a certain relevance in both computer science and cognitive psychology. Computer scientists usually analyze spatial dimensions in order to deal with automatic vision problems, such as feature extraction. Psychologists seem more interested in the temporal dimension of complexity, as a means to explore attentional models. Is it possible to define, by merging both approaches, a more general index of visual complexity? The aim of this paper is the definition of objective measures of image complexity that fits with the so named perceived time. Towards the end we have defined a fuzzy mathematical model of visual…
Network of Concepts and Ideas
We present the results of an experiment designed to investigate the way information is organized and stored in the human brain. In particular, we are using controlled stimuli to reverse engineer the networks of ideas and concepts in order to answer the following questions. (1) Are the networks of ideas and concepts in the human brain invoked by verbal and visual stimuli distinct from each other? The answer appears to be no for the network of ideas and inconclusive for the network of concepts. (2) What is the topology of these networks? Our experimental results show that both are small-world networks, with the network of ideas being random and the network of concepts scale-free.
Attentional vs computational complexity measures in observing paintings
Because of the great heterogeneity of subjects and styles, esthetic perception delineates a special and elusive field of research in vision, which represents an interesting challenge for cognitive science tools. With specific regard to the role of visual complexity, in this paper we present an experiment aimed to measure this dimension in a heterogeneous set of paintings. We compared perceived time complexity measures - based on a temporal estimation paradigm - with physical and statistical properties of the paintings, obtaining a strong correlation between psychological and computational results.
On the Evaluation of Images Complexity: A Fuzzy Approach
The inherently multidimensional problem of evaluating the complexity of an image is of a certain relevance in both computer science and cognitive psychology. Computer scientists usually analyze spatial dimensions, to deal with automatic vision problems, such as feature-extraction. Psychologists seem more interested in the temporal dimension of complexity, to explore attentional models. Is it possible, by merging both approaches, to define an more general index of visual complexity? We have defined a fuzzy mathematical model of visual complexity, using a specific entropy function; results obtained by applying this model to pictorial images have a strong correlation with ones from an experime…