Kansei-Based Color Balancing for Motion Graphics

Digital cameras, portable capture devices, smart phones, and tablets have become ubiquitous in daily life. The technologies in those devices can capture the digital copy of images and videos. The digitized copy is created for the purpose of digital manipulation and editing. Currently, many online and off-line software provide tools to manipulate and grading image colors. As the name implies, color balancing or color grading is a way of altering or adapting the color of the captured footages. Color balancing is performed to optimize source material, to focus attention on a key element in a shot, to correct errors in white balance and exposure, to ensure color consistency from one shot to another, or to create a color palette for a specific visual look desired by an artist. The most common criticism of color balancing tools is that provided interfaces and menus parameters have less perceptual meaning. The motion graphics artist has to improve an additional knowledge of the various theories in mathematics in order to control slider bars and curves in such an interface. An artist generally knows what his or her desired visual look for specific scene, without the requirement of understanding the several advanced theories of color manipulation. This means that often, perception of visual look is highly dependent on human Kansei. This is the main argument that we want to explore in this research. The study of color balancing or grading based on users´ Kansei has not yet been well researched. In this paper, we propose Kansei-based framework for color balancing in motion graphics.