Example-based human motion extrapolation based on manifold learning
MM '11 Proceedings of the 19th ACM international conference on Multimedia
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This paper presents an intuitive method for synthesizing videos by directly manipulating video objects without using 3D models. The proposed method extracts a video object from each video frame and creates locally consistent video sequences using a 2D motion graph, where its node corresponds to the extracted video object and its edge represents a motion transition between a pair of nodes. Our primary contribution lies in a sophisticated construction of the 2D motion graph using shape matching techniques, and its search that allows us to intuitively synthesize a new video sequence by manipulating feature points extracted from the video objects through the 2D screen space. The method further employs a deformation technique to interpolate between video objects with relatively different shapes, and thus can increase available motion transitions by inserting intervening video objects into the 2D motion graph. Several examples have been generated to demonstrate that this approach can create the user-intended motions of the video objects easily by clicking and dragging the feature points.