Measuring icon complexity: An automated analysis

Measures of icon designs rely heavily on surveys of the perceptions of population samples. Thus, measuring the extent to which changes in the structure of an icon will alter its perceived complexity can be costly and slow. An automated system capable of producing reliable estimates of perceived complexity could reduce development costs and time. Measures of icon complexity developed by Garcia, Badre, and Stasko (1994) and McDougall, Curry, and de Bruijn (1999) were correlated with six icon properties measured using Matlab (MathWorks, 2001) software, which uses image-processing techniques to measure icon properties. The six icon properties measured were icon foreground, the number of objects in an icon, the number of holes in those objects, and two calculations of icon edges and homogeneity in icon structure. The strongest correlates with human judgments of perceived icon complexity (McDougall et al., 1999) were structural variability (r(s) = .65) and edge information (r(s) =.64).

An Enactive Approach to the Design of New Tangible Musical Instruments

In this paper, we propose a theoretical framework for the design of tangible interfaces for musical expression. The main insight for the proposed approach is the importance and utility of familiar sensorimotor experiences for the creation of engaging and playable new musical instruments. In particular, we suggest exploiting the commonalities between different natural interactions by varying the auditory response or tactile details of the instrument within certain limits. Using this principle, devices for classes of sounds such as coarse grain collision interactions or friction interactions can be designed. The designs we propose retain the familiar tactile aspect of the interaction so that the performer can take advantage of tacit knowledge gained through experiences with such phenomena in the real world.