We investigated how shape features in natural images influence emotions aroused in human beings. Shapes and their characteristics such as roundness, angularity, simplicity, and complexity have been postulated to affect the emotional responses of human beings in the field of visual arts and psychology.However, no prior research has modeled the dimensionality of emotions aroused by roundness and angularity.Our contributions include an in-depth statistical analysis to understand the relationship between shapes and emotions. Through experimental results on the International Affective Picture System (IAPS) dataset we provide evidence for the significance of roundness-angularity and simplicitycomplexity on predicting emotional content in images. We combine our shape features with other state-of-theart features to show a gain in prediction and classification accuracy.We model emotions from a dimensional perspective in order to predict valence and arousal ratings which have advantages over modeling the traditional discrete emotional categories. Finally, we distinguish images with strong emotional content from emotionally neutral images with high accuracy.
In this paper we describe a comprehensive system to enhance the aesthetic quality of the photographs captured by the mobile consumers. The system, named OS-CAR, has been designed to provide on-site composition and aesthetics feedback through retrieved examples. We introduce three novel interactive feedback components. The first is the composition feedback which is qualitative in nature and responds by retrieving highly aesthetic exemplar images from the corpus which are similar in content and composition to the snapshot. The second is the color combination feedback which provides confidence on the snapshot to contain good color combinations. The third component is the overall aesthetics feedback which predicts the aesthetic ratings for both color and monochromatic images. An existing algorithm is used to provide ratings for color images, while new features and a new model are developed to treat monochromatic images. This system was designed keeping the next generation photography needs in mind and is the first of its kind. The feedback rendered is guiding and intuitive in nature. It is computed in situ while requiring minimal input from the user.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations鈥揷itations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.