The concept of visual balance is innate for humans, and influences how we perceive visual aesthetics and cognize harmony. Although visual balance is a vital principle of design and taught in schools of designs, it is barely quantified. On the other hand, with emergence of automantic/semi-automatic visual designs for self-publishing, learning visual balance and computationally modeling it, may escalate aesthetics of such designs. In this paper, we present how questing for understanding visual balance inspired us to revisit one of the well-known theories in visual arts, the so called theory of “visual rightness”, elucidated by Arnheim. We define Arnheim’s hypothesis as a design mining problem with the goal of learning visual balance from work of professionals. We collected a dataset of 120K images that are aesthetically highly rated, from a professional photography website. We then computed factors that contribute to visual balance based on the notion of visual saliency. We fitted a mixture of Gaussians to the saliency maps of the images, and obtained the hotspots of the images. Our inferred Gaussians align with Arnheim’s hotspots, and confirm his theory. Moreover, the results support the viability of the center of mass, symmetry, as well as the Rule of Thirds in our dataset.
Color theme (palette) is a collection of color swatches for representing or describing colors in a visual design or an image. Color palettes have broad applications such as serving as means in automatic/semi-automatic design of visual media, as measures in quantifying aesthetics of visual design, and as metrics in image retrieval, image enhancement, and color semantics. In this paper, we suggest an autonomous mechanism for extracting color palettes from an image. Our method is simple and fast, and it works on the notion of visual saliency. By using visual saliency, we extract the fine colors appearing in the foreground along with the various colors in the background regions of an image. Our method accounts for defining different numbers of colors in the palette as well as presenting the proportion of each color according to its visual conspicuity in a given image. This flexibility supports an interactive color palette which may facilitate the designer’s color design task. As an application, we present how our extracted color palettes can be utilized as a color similarity metric to enhance the current color semantic based image retrieval techniques.
In the design of a magazine cover, making a set of decisions regarding the color distribution of the cover image and the colors of other graphical and textual elements is considered to be the concept of color design. This concept addresses a number of subjective challenges, specifically how to determine a set of colors that is aesthetically pleasing yet also contributes to the functionality of the design, the legibility of textual elements, and the stylistic consistency of the class of magazine. Our solution to automatic color design includes the quantification of these challenges by deploying a number of well-known color theories. These color theories span both color harmony and color semantics. The former includes a set of geometric structures that suggest which colors are in harmony together. The latter suggests a higher level of abstraction. Color semantics means to bridge sets of color combinations with color mood descriptors. For automatic design, we aim to deploy these two viewpoints by applying geometric structures for the design of text color and color semantics for the selection of cover images.
In this paper, we propose a system for automatic design of magazine covers that quantifies a number of concepts from
art and aesthetics. Our solution to automatic design of this type of media has been shaped by input from professional
designers, magazine art directors and editorial boards, and journalists. Consequently, a number of principles in design
and rules in designing magazine covers are delineated. Several techniques are derived and employed in order to quantify
and implement these principles and rules in the format of a software framework. At this stage, our framework divides the
task of design into three main modules: layout of magazine cover elements, choice of color for masthead and cover lines,
and typography of cover lines. Feedback from professional designers on our designs suggests that our results are
congruent with their intuition.