Snapshots of complexity: using motion capture and principal component analysis to reconceptualize dance

Abstract

This article brings together the disparate worlds of dance practice, motion capture and statistical analysis. Digital technologies such as motion capture offer dance artists new processes for recording and studying dance movement. Statistical analysis of these data can reveal hidden patterns in movement in ways that are semantically ‘blind’, and are hence able to challenge accepted culturo-physical ‘grammars’ of dance creation. The potential benefit to dance artists is to open up new ways of understanding choreographic movement. However, quantitative analysis does not allow for the uncertainty inherent in emergent, artistic practices such as dance. This article uses motion capture and principal component analysis (PCA), a common statistical technique in human movement recognition studies, to examine contemporary dance movement, and explores how this analysis might be interpreted in an artistic context to generate a new way of looking at the nature and role of movement patterning in dance creation.