Video Based Motion Synthesis by Splicing and Morphing

In this paper we present a method for synthesizing videos of human motion by splicing together clips of input video. There are two main contributions in this work. The first is developing a method for “kinematically correct morphing” of images of human figure, which is used to splice together the clips in input video in a manner that produces smooth output sequences. The second contribution of this work is the application of activity recognition algorithms to our input data in order to automatically extract action labels, which allow us to control the synthesized video by issuing high-level action commands. We present results of synthetic sequences on two domains: ballet and tennis.

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