Spreadsheets for Images
Marc Levoy, Dept. of Computer Science, Stanford
levoy@cs.stanford.eduSeminar on People, Computers, and Design
Stanford University September 30, 1994
The majority of commercially available image processing and data visualization systems employ a dataflow paradigm. Users select modules from a menu and wire them together using an interactive flow chart editor.
I will describe an alternative paradigm based on spreadsheets. Cells in such a spreadsheet contain graphical objects such as images, volumes, or movies. Cells may also contain graphical widgets such as buttons, sliders, or movie viewers. Objects are displayed in miniature inside each cell. Formulas for cells are written in a programming language that includes operators for array manipulation, image processing, and rendering. Formulas may also contain control structures, procedure calls, and assignment operators with side effects.
Compared to flow chart visualization systems, spreadsheets are more expressive, more scalable, and easier to program. Compared to numerical spreadsheets, spreadsheets for images pose several unique design problems: larger formulas, longer computation times, and more complicated intercell dependencies. We describe an implementation based on the Tcl programming language and the Tk widget set, and we discuss our solutions to these design problems. We also point out some unexpected uses for our spreadsheets: as a visual database browser, as a graphical user interface builder, as a smart clipboard for the desktop, and as a presentation tool.
Marc Levoy is an assistant professor of Computer Science and Electrical Engineering at Stanford University. He received a B. Architecture in 1976 from Cornell University, an M.S. in 1978 from Cornell University, and a Ph.D. in Computer Science in 1989 from the University of North Carolina at Chapel Hill. He was principal developer of the Hanna-Barbera Computer Animation System and served as its director from 1980 through 1983. He has published over thirty papers on computer animation, volume visualization, and medical imaging. His current research interests include visualization of multidimensional sampled data, digitization of 3D objects using active sensing technologies, and the design of languages and user interfaces for data visualization. Professor Levoy received the NSF Presidential Young Investigator Award in 1991.
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