Foundations of Computational Visualistics (review)

Some years ago, the department of computer science at the University of Magdeburg developed a completely new degree program called Computational Visualistics as an alternative to studies in digital media. Visualistics is a blend of visual and linguistic studies that includes how humans express what they perceive, feel, experience and create with their computational mediations. It has points of intersection also with a myriad of fields, such as computer vision, cognitive science, communication, mathematics, neuroscience, philosophy, psychology, history of art, aesthetics and semiotics. This book is conceived as a map of questions, such as what images are for computer science and their uses. Other topics treated in the book include image processing, object models, interactivity, image databases, virtual architecture and mental images.

Inside one can find an introduction to the old concerns regarding the relationship between symbol and icon, word and image, chains of signs and the field of signs, time and space that have caused different degrees of unrest, and academic, cultural and religious quarrels throughout the years. Our symbols will continue to question our concepts of the universal and the particular, material and spiritual and our current scientific paradigms.

Schirra also explains how images have become a central part of our culture that not only transforms information but also connects and simultaneously separates people. There are discussions about various aspects of the image such as resemblance, mimicry, perception, reflection and deception. Foundations of Computational Visualistics has practical information for computational graphics and interactive installations. The main interest is not just data but the process of acquiring knowledge and its scientific application in a communicational context.

It is common to have discussions about whether text is more adequate to represent reality and acquire knowledge or if it has an unfair prevalence over the image both in text-based computer code and academic discourse. The text in the book uses word signs in order to understand picture signs. The book does not favor word over image or vice versa but deals with the formalization of what can be called an image data type that deals with pictures represented by algorithmic artifacts borrowing some linguistic terms, such as syntax, the order of words; semantics, the meaning of words; and pragmatics, the use of language for communication in a social context. Thus, the data type "image" is defined using picture syntax, which deals with image processing and the order of pixels; picture semantics, which deals with geometric models, visual gestalts and computer vision assimilated as "image understanding"; and finally picture pragmatics, which deals with authenticity (whether the apparent sender of a message is the real sender or not) and interactivity.

The general approach is hybrid, but it is more focused towards graphic engineers. It also concisely analyzes some interactive artworks in Chapter 4, entitled "The Generic Data Type 'Image': General Aspects," under the section Pragmatic Aspects, and in Chapter 5, "Case Studies: Using the Data Type 'Image,' " in particular A Border Line Case: Immersion. The artworks displayed are from Picasso, Escher and, later on, Char Davies and Harold Cohen, Frieder Nake, Jane Prophet, Manfred Mohr, Perry Hober-man, Tom Banks and Melinda Rack-man. It would be up to artists to find the relationship between the concepts of computational visualistics and other artworks not included in the text, such as Christa Sommerer's Verbarium, David Rokeby's The Giver of Names, Jeffery Shaw's The Legible City, Camille Utter-back's Text Rain, The Apartment by Marek Walzac and Martin Wattenberg, Mark Hansen and Ben Rubin's Listening Post, Jenny Holzer, Young Hae-Chang and many other artists who work at the crossroads of language and image.

The book has a good deal of both new and specialized terminology and so is suitable for a class curriculum in the topic that can expand the ideas described with more examples. Although one can find algorithms for image processing and information visualization, it is not necessary to have a deep mathematical background to read it.