Expressive

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Browsing Expressive by Subject "Motion processing"

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    MVAE : Motion-conditioned Variational Auto-Encoder for tailoring character animations
    (The Eurographics Association, 2025) Bordier, Jean-Baptiste; Christie, Marc; Catalano, Chiara Eva; Parakkat, Amal Dev
    The design of character animations with enough diversity is a time-consuming task in many productions such as video games or animated films, and drives the need for more simple and effective authoring systems. This paper introduces a novel approach, a motion-conditioned variational autoencoder (VAE) with Virtual reality as a motion capture device. Our model generates diverse humanoid character animations only based on a gesture captured from two Virtual reality controllers, allowing for precise control of motion characteristics such as rhythm, speed and amplitude, and providing variability through noise sampling. From a dataset comprising paired controller-character motions, we design and train our VAE to (i) identify global motion characteristics from the movement, in order to discern the type of animation desired by the user, and (ii) identify local motion characteristics including rhythm, velocity, and amplitude to adapt the animation to these characteristics. Unlike many text-tomotion approaches, our method faces the challenge of interpreting high-dimensional, non-discrete user inputs. Our model maps these inputs into the higher-dimensional space of character animation while leveraging motion characteristics (such as height, speed, walking step frequency, and amplitude) to fine-tune the generated motion. We demonstrate the relevance of the approach on a number of examples and illustrate how changes in rhythm and amplitude of the input motions are transferred to coherent changes in the animated character, while offering a diversity of results using different noise samples.
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    Video Motion Stylization by 2D Rigidification
    (The Eurographics Association, 2019) Delanoy, Johanna; Bousseau, Adrien; Hertzmann, Aaron; Kaplan, Craig S. and Forbes, Angus and DiVerdi, Stephen
    This paper introduces a video stylization method that increases the apparent rigidity of motion. Existing stylization methods often retain the 3D motion of the original video, making the result look like a 3D scene covered in paint rather than a 2D painting of a scene. In contrast, traditional hand-drawn animations often exhibit simplified in-plane motion, such as in the case of cut-out animations where the animator moves pieces of paper from frame to frame. Inspired by this technique, we propose to modify a video such that its content undergoes 2D rigid transforms. To achieve this goal, our approach applies motion segmentation and optimization to best approximate the input optical flow with piecewise-rigid transforms, and re-renders the video such that its content follows the simplified motion. The output of our method is a new video and its optical flow, which can be fed to any existing video stylization algorithm.