Natural Motion Stitching

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Overview

Given two motion-capture sequences that are to be stitched together, how can we assess the goodness of the stitching? The straightforward solution, Euclidean distance, permits counter-intuitive results because it ignores the effort required to actually make the stitch. The main contribution of our work is that we propose an intuitive, first-principles approach, by computing the effort that is needed to do the transition (laziness-effort, or íL-score').

Our conjecture is that, the smaller the effort, the more natural the transition will seem to humans. Moreover, we propose the elastic L-score which allows for elongated stitching, to make a transition as natural as possible. We present preliminary experiments on both artificial and real motions which show that our L-score approach indeed agrees with human intuition, it chooses good stitching points, and generates natural transition paths.

FUNDING ACKNOWLEDGEMENTS:
This material is based upon work supported by the National Science Foundation under Grants No. IIS-0326322 and ECS-0325383. The data used in this project was obtained from mocap.cs.cmu.edu supported by NSF EIA-0196217. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation, or other funding parties.

People

Publication

Lei Li, James McCann, Christos Faloutsos and Nancy Pollard. Laziness is a virtue: Motion stitching using effort minimization. Euro Graphics 2008 (short paper). [BiBTeX]

Download

         Processed motion capture dataset,  hand waving dataset [67MB]

         Other motion capture data used in the paper, see subject #16 [here]

Demo

            (mp4 format) [Download]