Application of the Bayesian information criterion to keyframe extraction from motion capture data

In most of the techniques to extract keyframes from motion capture (mocap) data, criteria to guarantee the quality of keyframes are provided by manually adjusting evaluation parameters. In this study, the authors try to apply the Bayesian information criterion (BIC) [Schwartz 1978] to keyframe extraction. BIC is a model-selection criterion; models are evaluated under the tradeoff between the goodness of fit to observed data and the model complexity. Applying BIC allows us to automatically asses the quality of keyframes under the tradeoff between the accuracy of interpolated motions and the reduction of the number of keyframes.