Knowledge discovery in choreographic data using Relative Motion matrices and Dynamic Time Warping

• We visualize and analyze the motion patterns of samba dancers during their performance.
• The motion patterns are formed on the basis of different motion attributes, such as speed and motion azimuth.
• REMO and DTW are both used to explore the motion patterns.

Recent advances in location-aware technologies have led to the exploitation of geospatial methods to uncover valuable information from large movement data sets. The focus of this study is on choreographic data. In particular, the goal of the study is to visualize and analyze the motion patterns of samba dancers during their performance by means of two complementary methods. The first method performs map algebra with RElative MOtion (REMO) matrices to study the evolution of motion attributes, such as speed, motion azimuth, and vertical angle over time. The second method applies Dynamic Time Warping (DTW) to time series of motion attributes. The results demonstrate that both methods are useful in numerically comparing the performance of samba dancers and visually exploring the motion patterns of different body parts.