Most motion editing techniques require significant computation resources or considerable manual annotation. This thesis proposes analytical classification and correspondence techniques to support consistent interpolation between pairs or quadruples of motion clips. The main contributions are: a) Motion clips are labeled with locomotion and generic kinematic joint level events; b) These event labels are gathered into states during inter-motion correspondence; c) An efficient globally optimal correspondence between states is performed, preserving state sequences; d) Weights gathered from a spline function drive a frequency and spatial domain motion transition, preserving locomotion contact constraints. The thesis extensively examines the application of the framework to a wide variety of motions, unlike peer methods. It proves the limitations of widely cited low-level signal-correspondence techniques in addressing transitions between different types of motions; e.g. running and dancing. Useful additions include unlimited motion chains and decoupled upperbody-lowerbody interpolations. Key results and comparisons have been posted at http://www.comp.nus.edu.sg/~ashraf/framespace

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