Motion capture sessions typically produce long streams of motion capture data, but many motion capture applications, such as gesture recognition, gait analysis, and motion retargeting, require small, discrete, logical segments of motion capture in order to function properly. Motion capture segmentation is the process of breaking up motion capture data into small pieces that are appropriate for an analysis tool.
Giving computers the ability to better understand users could lead to software that is able to adapt to individual users, and therefore become easier to use. Laban Movement Analysis (LMA) is a formal system for labeling and describing movement. By using machine learning techniques to classify LMA Effort parameters it is possible to produce a real-time qualitative analysis of human motion.