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This paper proposes a new method for facial motion extraction to represent, learn and recognize observed expressions, from 4D video sequences. The approach called Deformation Vector Field (DVF) is based on Riemannian facial shape analysis and captures densely dynamic information from the entire face. The resulting temporal vector field is used to build the feature vector for expression recognition...
We describe a new method to relieve common assumptions/ restrictions in head tracking by using a model-based approach. This improves local feature matching which only considers the pattern around the extracted feature excluding the object shape, so that misalignment can occur. In this paper, to overcome constraints on motion we consider region- and distance-based feature refinement methods to validate...
We propose a new framework for recognizing three-dimensional (3D) objects that needs few reference images. We tackle a key issue of 3D object recognition; the trade-off between the number of reference images and recognition accuracy. We assume that a reference image is a photo of the object from an arbitrary position, typical of those used to exhibit goods on the web. The framework, first, estimates...
In this paper, we introduce a puppet interface for the development of an intuitive animation system. Our puppet interface does not require any special devices and any type of puppet can be used. The puppet interface is developed by attaching ten visible markers onto a puppet. The user can manipulate the pose of the puppet interface to produce the desired motion in front of a camera. The puppet's joint...
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