J
Jaume Rigau
Researcher at University of Girona
Publications - 34
Citations - 778
Jaume Rigau is an academic researcher from University of Girona. The author has contributed to research in topics: Mutual information & Information theory. The author has an hindex of 16, co-authored 34 publications receiving 726 citations.
Papers
More filters
Journal ArticleDOI
Informational Aesthetics Measures
TL;DR: A set of ratios based on information theory and Kolmogorov complexity that can help to quantify the aesthetic experience are defined.
Journal ArticleDOI
Computational Aesthetics 2008: Categorizing art: Comparing humans and computers
Christian Wallraven,Roland W. Fleming,Douglas W. Cunningham,Jaume Rigau,Miquel Feixas,Mateu Sbert +5 more
TL;DR: Using several state-of-the-art algorithms from computer vision, it is found that whereas low-level appearance information can give some clues about category membership, human grouping strategies included also much higher-level concepts.
Proceedings ArticleDOI
Conceptualizing Birkhoff's aesthetic measure using Shannon entropy and Kolmogorov complexity
TL;DR: The Birkhoff's Aesthetic Measure is presented as the ratio between the algorithmic reduction of uncertainty (order) and the initial uncertainty (complexity) of the image, and the measures proposed are applied to several works of Mondrian, Pollock, and van Gogh.
Proceedings ArticleDOI
An information-theoretic framework for image complexity
TL;DR: A new information-theoretic approach to study the complexity of an image is introduced, based on considering the information channel that goes from the histogram to the regions of the partitioned image, maximizing the mutual information.
Journal ArticleDOI
Image Segmentation Using Information Bottleneck Method
TL;DR: This paper introduces a split-and-merge algorithm based on the definition of an information channel between a set of regions of the image and the intensity histogram bins and presents two new clustering algorithms which show how the information bottleneck method can be applied to the registration channel obtained when two multimodal images are correctly aligned.