Who's Afraid of Itten
Published 13 October 2015
Andreza Sartori, Dubravko Ćulibrk, Yan Yan, Nicu Sebe
Citations53
Generate an AI Snapshot to get a quick, structured summary of this paper.
Study Snapshot
ObjectiveStudy objective
MethodsResearch methodology
PopulationPopulation studied
Sample sizeSample sizes
OutcomesStudy outcomes here
ResultsStudy results comes here
LimitationsResearch study limitations comes here
A concise AI-generated summary of the paper will appear here once you click Generate AI Snapshot.
TL;DR
This work proposes a novel computational approach able to analyze the color combinations in abstract paintings and use this information to infer whether a painting will evoke positive or negative emotions in an observer, and exploits art theory concepts to design the features and the learning algorithm.
Abstract
Color plays an essential role in everyday life and is one of the most important visual cues in human perception. In abstract art, color is one of the essential means to convey the artist's intention and to affect the viewer emotionally. However, colors are rarely experienced in isolation, rather, they are usually presented together with other colors. In fact, the expressive properties of two-color combinations have been extensively studied by artists. It is intriguing to try to understand how color combinations in abstract paintings might affect the viewer emotionally, and to investigate if a computer algorithm can learn this mechanism.
Keywords
PsychologyNeurosciencePhysics and Astronomy
International Journal of Computer VisionEfficient Graph-Based Image Segmentation
6,198 Citations2004Pedro F. Felzenszwalb, Daniel P. Huttenlocher
An efficient segmentation algorithm is developed based on a predicate for measuring the evidence for a boundary between two regions using a graph-based representation of the image and it is shown that although this algorithm makes greedy decisions it produces segmentations that satisfy global properties.
Affective image classification using features inspired by psychology and art theory
841 Citations2010Jana Machajdik, Allan Hanbury
This work investigates and develops methods to extract and combine low-level features that represent the emotional content of an image, and uses these for image emotion classification.
IEEE Transactions on Image ProcessingLearning Color Names for Real-World Applications
718 Citations2009Joost van de Weijer, C. Schmid +2 more
Experimental results show that colorNames learned from real-world images significantly outperform color names learned from labeled color chips for both image retrieval and image annotation.
Concerning the Spiritual in Art
649 Citations1977Wassily Kandinsky
Color Research & ApplicationA study of colour emotion and colour preference. Part I: Colour emotions for single colours
646 Citations2004Li‐Chen Ou, Ming Ronnier Luo +2 more
The MIT Press eBooksTrueSkill™: A Bayesian Skill Rating System
625 Citations2007Ralf Herbrich, Tom Minka +1 more
A new Bayesian skill rating system which can be viewed as a generalisation of the Elo system used in Chess, which tracks the uncertainty about player skills, explicitly models draws, can deal with any number of competing entities and can infer individual skills from team results.
Exploring Principles-of-Art Features For Image Emotion Recognition
364 Citations2014Sicheng Zhao, Yue Gao +4 more
Experiments demonstrate the superiority of PAEF for affective image classification and regression (with about 5% improvement on classification accuracy and 0.2 decrease in mean squared error), as compared to the state-of-the-art approaches.
The art of color : the subjective experience and objective rationale of color
314 Citations1961Johannes Itten
Vision and Art: The Biology of Seeing
277 Citations2002Margaret S. Livingstone, David H. Hubel
The future begins with this book, which demonstrates that how the authors see art depends ultimately on the cells in their eyes and their brains.
Color attributes for object detection
266 Citations2012Fahad Shahbaz Khan, Rao Muhammad Anwer +4 more
This paper proposes the use of color attributes as an explicit color representation for object detection and shows that this method improves over state-of-the-art techniques despite its simplicity.
Color Research & ApplicationA study of colour emotion and colour preference. Part II: Colour emotions for two‐colour combinations
230 Citations2004Li‐Chen Ou, Ming Ronnier Luo +2 more
Emotional valence categorization using holistic image features
197 Citations2008Victoria Yanulevskaya, Jan C. van Gemert +4 more
An emotion categorization system, trained by ground truth from psychology studies, based on the assessment of local image statistics which are learned per emotional category using support vector machines is proposed.
Discriminative Color Descriptors
121 Citations2013Rahat Khan, Joost van de Weijer +4 more
This paper cluster color values together based on their discriminative power in a classification problem, and shows that the proposed descriptor outperforms existing photometric invariants and combined with shape description these color descriptors obtain excellent results on four challenging datasets.
No Matter Where You Are: Flexible Graph-Guided Multi-task Learning for Multi-view Head Pose Classification under Target Motion
114 Citations2013Yan Yan, Elisa Ricci +3 more
A novel Multi-Task Learning framework that achieves state-of-the-art classification with few training data, FEGA-MTL operates on a dense uniform spatial grid and learns appearance relationships across partitions as well as partition-specific appearance variations for a given head pose to build region-specific classifiers.
In the eye of the beholder
101 Citations2012Victoria Yanulevskaya, Jasper Uijlings +6 more
This work considers a set of 500 abstract paintings from Museum of Modern and Contemporary Art of Trento and Rovereto (MART), where each painting was scored as carrying a positive or negative response on a Likert scale of 1-7, and dissects the classification machinery to determine which parts of an image evokes what emotions.
Choice Reviews OnlineInventing abstraction, 1910-1925: how a radical idea changed modern art
95 Citations2013
ACM Transactions on Interactive Intelligent SystemsAffective Analysis of Professional and Amateur Abstract Paintings Using Statistical Analysis and Art Theory
49 Citations2015Andreza Sartori, Victoria Yanulevskaya +4 more
This work employs a state-of-the-art recognition system to learn which statistical patterns are associated with positive and negative emotions on two different datasets that comprise professional and amateur abstract artworks, and uses computer vision techniques to quantify which parts of a painting evoke positive andnegative emotions.
Institutional Research Information System (Università degli Studi di Trento)Inferring painting style with multi-task dictionary learning
24 Citations2015Gaowen Liu, Yan Yan +5 more
This paper presents a novel dictionary learning approach to automatically uncover the artistic style from paintings, by automatically decoupling style-specific and artist-specific patterns, and shows that this approach significantly outperforms state-of-the-art methods.
Institutional Research Information System (Università degli Studi di Trento)Looking at Mondrian's victory Boogie-Woogie: what do i feel?
12 Citations2015Andreza Sartori, Yan Yan +4 more
A novel joint flexible Schatten p- norm model is proposed which can exploit the sharing patterns between visual and textual information for abstract painting emotion analysis and a qualitative analysis is conducted on the cases in which metadata help improving the machine performance.