Optimizing computer imagery for more effective visual communication
Bruce Gooch, Vidya Setlur · 2005
Computers are becoming faster, smaller, and more interconnected, creating a shift in their primary function from computation to communication. This trend is exemplified by ubiquitous devices such as cellular phones with cameras, personal digital assistants with video, information displays in automobiles, and computer screens in elevators and refrigerators. At the same time, progress in networking and storage technologies allows large quantities of image and video data to be provided whenever desired. Rapid advances in technology allow computer screens to be filled with complex information at real-time rates. Simulations that once required supercomputers are commonly run on desktop applications. While the computer industry has produced faster processors, larger disk drives, and higher memory capacity, these advances do little to help people understand the meaning and representation of data. This lack of understanding stems from the fact machines process data in numerical form, while humans comprehend visual data more easily. As communication infrastructure and viewing situations become more plentiful, we need imagery that facilitates visual communication across a wide range of display devices. In addition, producing effective and expressive visual content currently requires considerable artistic skill and can consume days. The goal of my research is to develop new algorithms and user interfaces that enhance visual communication, while making it fast and easy to generate compelling content. My research combines concepts and methods from visual art, perceptual psychology, information processing and cognitive science to facilitate users in creating, understanding, and interpreting computer imagery. In conformance to these goals, my research includes retargeting large images for smaller displays by maximizing the recognizability of more important features in the retargeted images, and generating new file icons that better reveal the files' intent or purpose. This dissertation presents three techniques for automatically retargeting imagery to smaller displays and desktop interfaces: (1) An image retargeting method for adapting photographs to smaller display sizes. (2) A technique for generating more meaningful desktop file icons. (3) A vector graphics approach for retargeting animation and informational images to smaller display sizes.